added chrf scores, small bug in translation thinking it has to do with special chars

eng-nah-svo-translation/README.md

@@ -16,8 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3041
-- Bleu: 0.0
+- Loss: 0.2640
+- Bleu: 0.0231
+- Chrf: 26.4891
 
 ## Model description
 

eng-nah-svo-translation/checkpoint-228/optimizer.pt

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eng-nah-svo-translation/checkpoint-228/pytorch_model.bin

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eng-nah-svo-translation/checkpoint-228/trainer_state.json

@@ -12,7 +12,7 @@
   "max_steps": 684,
   "num_train_epochs": 3,
   "save_steps": 500,
-  "total_flos": 50445004308480.0,
+  "total_flos": 52376151785472.0,
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 }

eng-nah-svo-translation/checkpoint-228/training_args.bin

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eng-nah-svo-translation/checkpoint-456/optimizer.pt

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eng-nah-svo-translation/checkpoint-456/pytorch_model.bin

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eng-nah-svo-translation/checkpoint-456/trainer_state.json

@@ -12,7 +12,7 @@
   "max_steps": 684,
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   "save_steps": 500,
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+  "total_flos": 104753362894848.0,
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 }

eng-nah-svo-translation/checkpoint-456/training_args.bin

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eng-nah-svo-translation/checkpoint-684/optimizer.pt

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eng-nah-svo-translation/checkpoint-684/pytorch_model.bin

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eng-nah-svo-translation/checkpoint-684/trainer_state.json

@@ -11,7 +11,7 @@
     {
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       "learning_rate": 5.380116959064328e-06,
-      "loss": 0.2276,
+      "loss": 0.1428,
       "step": 500
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@@ -19,7 +19,7 @@
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+  "total_flos": 156851971817472.0,
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   "trial_params": null
 }

eng-nah-svo-translation/checkpoint-684/training_args.bin

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eng-nah-svo-translation/pytorch_model.bin

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eng-nah-svo-translation/training_args.bin

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myerrors_1551.out

@@ -1,34 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-Using pad_token, but it is not set yet.
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 130, in <module>
-    trainer.evaluate(max_length=max_length)
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 159, in evaluate
-    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 2972, in evaluate
-    output = eval_loop(
-             ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 3151, in evaluation_loop
-    for step, inputs in enumerate(dataloader):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/accelerate/data_loader.py", line 384, in __iter__
-    current_batch = next(dataloader_iter)
-                    ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
-    data = self._next_data()
-           ^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 677, in _next_data
-    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/_utils/fetch.py", line 54, in fetch
-    return self.collate_fn(data)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/data/data_collator.py", line 586, in __call__
-    features = self.tokenizer.pad(
-               ^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/tokenization_utils_base.py", line 3059, in pad
-    padding_strategy, _, max_length, _ = self._get_padding_truncation_strategies(
-                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/tokenization_utils_base.py", line 2507, in _get_padding_truncation_strategies
-    raise ValueError(
-ValueError: Asking to pad but the tokenizer does not have a padding token. Please select a token to use as `pad_token` `(tokenizer.pad_token = tokenizer.eos_token e.g.)` or add a new pad token via `tokenizer.add_special_tokens({'pad_token': '[PAD]'})`.

myerrors_1552.out

@@ -1,29 +0,0 @@
-
-
-
-
-
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 131, in <module>
-    trainer.evaluate(max_length=max_length)
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 159, in evaluate
-    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 2972, in evaluate
-    output = eval_loop(
-             ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 3161, in evaluation_loop
-    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
-                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 282, in prediction_step
-    generated_tokens = self.model.generate(**inputs, **gen_kwargs)
-                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
-    return func(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1402, in generate
-    self._validate_model_class()
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1197, in _validate_model_class
-    raise TypeError(exception_message)
-TypeError: The current model class (BertModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'BertLMHeadModel'}

myerrors_1553.out

@@ -1,25 +0,0 @@
-
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 131, in <module>
-    trainer.evaluate(max_length=max_length)
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 159, in evaluate
-    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 2972, in evaluate
-    output = eval_loop(
-             ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 3161, in evaluation_loop
-    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
-                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 282, in prediction_step
-    generated_tokens = self.model.generate(**inputs, **gen_kwargs)
-                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
-    return func(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1402, in generate
-    self._validate_model_class()
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1197, in _validate_model_class
-    raise TypeError(exception_message)
-TypeError: The current model class (BertModel) is not compatible with `.generate()`, as it doesn't have a language model head. Please use one of the following classes instead: {'BertLMHeadModel'}

myerrors_1554.out

@@ -1,165 +0,0 @@
-
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [18,0,0], thread: [0,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 131, in <module>
-    trainer.evaluate(max_length=max_length)
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 159, in evaluate
-    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 2972, in evaluate
-    output = eval_loop(
-             ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 3161, in evaluation_loop
-    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
-                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 282, in prediction_step
-    generated_tokens = self.model.generate(**inputs, **gen_kwargs)
-                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
-    return func(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1596, in generate
-    return self.greedy_search(
-           ^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 2444, in greedy_search
-    outputs = self(
-              ^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 1235, in forward
-    outputs = self.bert(
-              ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 1022, in forward
-    encoder_outputs = self.encoder(
-                      ^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 612, in forward
-    layer_outputs = layer_module(
-                    ^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 497, in forward
-    self_attention_outputs = self.attention(
-                             ^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 427, in forward
-    self_outputs = self.self(
-                   ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 286, in forward
-    mixed_query_layer = self.query(hidden_states)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/linear.py", line 114, in forward
-    return F.linear(input, self.weight, self.bias)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-RuntimeError: CUDA error: CUBLAS_STATUS_NOT_INITIALIZED when calling `cublasCreate(handle)`
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [161,0,0], thread: [96,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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myerrors_1555.out

@@ -1,46 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
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-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 261, in hf_raise_for_status
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/requests/models.py", line 1021, in raise_for_status
-    raise HTTPError(http_error_msg, response=self)
-requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/aatherton2024/eng-nah-svo-cpt/resolve/main/config.json
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 428, in cached_file
-    resolved_file = hf_hub_download(
-                    ^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1230, in hf_hub_download
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1606, in get_hf_file_metadata
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 271, in hf_raise_for_status
-huggingface_hub.utils._errors.EntryNotFoundError: 404 Client Error. (Request ID: Root=1-650786ae-6603d136738db081161c4861;1f95ec5e-e41f-4227-9312-c914e4df78c5)
-
-Entry Not Found for url: https://huggingface.co/aatherton2024/eng-nah-svo-cpt/resolve/main/config.json.
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 152, in <module>
-    model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
-            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 482, in from_pretrained
-    config, kwargs = AutoConfig.from_pretrained(
-                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py", line 1007, in from_pretrained
-    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
-                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 620, in get_config_dict
-    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
-                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 675, in _get_config_dict
-    resolved_config_file = cached_file(
-                           ^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 479, in cached_file
-    raise EnvironmentError(
-OSError: aatherton2024/eng-nah-svo-cpt does not appear to have a file named config.json. Checkout 'https://huggingface.co/aatherton2024/eng-nah-svo-cpt/main' for available files.

myerrors_1556.out

@@ -1,22 +0,0 @@
-
-
-
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 72, in <module>
-    model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
-            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 482, in from_pretrained
-    config, kwargs = AutoConfig.from_pretrained(
-                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py", line 1007, in from_pretrained
-    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
-                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 620, in get_config_dict
-    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
-                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 675, in _get_config_dict
-    resolved_config_file = cached_file(
-                           ^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 399, in cached_file
-    raise EnvironmentError(
-OSError: eng-nah-svo-cpt does not appear to have a file named config.json. Checkout 'https://huggingface.co/eng-nah-svo-cpt/None' for available files.

myerrors_1557.out

@@ -1,40 +0,0 @@
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 261, in hf_raise_for_status
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/requests/models.py", line 1021, in raise_for_status
-    raise HTTPError(http_error_msg, response=self)
-requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/eng-nah-svo-cpt/resolve/main/tokenizer_config.json
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 428, in cached_file
-    resolved_file = hf_hub_download(
-                    ^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1344, in hf_hub_download
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1230, in hf_hub_download
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1606, in get_hf_file_metadata
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 293, in hf_raise_for_status
-huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-65078ad3-69f0105f790b8b472eceb3d6;305708a1-7612-4fce-92cd-fb302d6700cd)
-
-Repository Not Found for url: https://huggingface.co/eng-nah-svo-cpt/resolve/main/tokenizer_config.json.
-Please make sure you specified the correct `repo_id` and `repo_type`.
-If you are trying to access a private or gated repo, make sure you are authenticated.
-
-The above exception was the direct cause of the following exception:
-
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 40, in <module>
-    tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
-                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/tokenization_auto.py", line 677, in from_pretrained
-    tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs)
-                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/tokenization_auto.py", line 510, in get_tokenizer_config
-    resolved_config_file = cached_file(
-                           ^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 449, in cached_file
-    raise EnvironmentError(
-OSError: eng-nah-svo-cpt is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
-If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>`

myerrors_1558.out

@@ -1,101 +0,0 @@
-
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [0,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [1,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [2,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [3,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [4,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [5,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [6,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [7,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [8,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [9,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [10,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [11,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [12,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [13,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [14,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [15,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [16,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [17,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [18,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [19,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [20,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [21,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [26,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [27,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [28,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [29,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [30,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-/opt/conda/conda-bld/pytorch_1682343995622/work/aten/src/ATen/native/cuda/Indexing.cu:1146: indexSelectLargeIndex: block: [237,0,0], thread: [31,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 132, in <module>
-    trainer.evaluate(max_length=max_length)
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 159, in evaluate
-    return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 2972, in evaluate
-    output = eval_loop(
-             ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer.py", line 3161, in evaluation_loop
-    loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
-                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/trainer_seq2seq.py", line 282, in prediction_step
-    generated_tokens = self.model.generate(**inputs, **gen_kwargs)
-                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
-    return func(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 1596, in generate
-    return self.greedy_search(
-           ^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/generation/utils.py", line 2444, in greedy_search
-    outputs = self(
-              ^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 1235, in forward
-    outputs = self.bert(
-              ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 1022, in forward
-    encoder_outputs = self.encoder(
-                      ^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 612, in forward
-    layer_outputs = layer_module(
-                    ^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 497, in forward
-    self_attention_outputs = self.attention(
-                             ^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 427, in forward
-    self_outputs = self.self(
-                   ^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/bert/modeling_bert.py", line 286, in forward
-    mixed_query_layer = self.query(hidden_states)
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
-    return forward_call(*args, **kwargs)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/nn/modules/linear.py", line 114, in forward
-    return F.linear(input, self.weight, self.bias)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-RuntimeError: CUDA error: CUBLAS_STATUS_NOT_INITIALIZED when calling `cublasCreate(handle)`

myerrors_1559.out

@@ -1,3 +0,0 @@
-
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-
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myerrors_1560.out

@@ -1,2 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-
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myerrors_1561.out

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-
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-/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
-  warnings.warn(
-/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
-
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-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 219, in <module>
-    for batch in tqdm(eval_dataloader):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/tqdm/std.py", line 1178, in __iter__
-    for obj in iterable:
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/accelerate/data_loader.py", line 394, in __iter__
-    next_batch = next(dataloader_iter)
-                 ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
-    data = self._next_data()
-           ^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 677, in _next_data
-    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/_utils/fetch.py", line 54, in fetch
-    return self.collate_fn(data)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/data/data_collator.py", line 600, in __call__
-    decoder_input_ids = self.model.prepare_decoder_input_ids_from_labels(labels=features["labels"])
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 1527, in prepare_decoder_input_ids_from_labels
-    return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 66, in shift_tokens_right
-    shifted_input_ids[:, 0] = decoder_start_token_id
-    ~~~~~~~~~~~~~~~~~^^^^^^
-IndexError: index 0 is out of bounds for dimension 1 with size 0
-
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myerrors_1562.out

@@ -1,8 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-
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-
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-/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
-  warnings.warn(
-/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
-
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myerrors_1563.out

@@ -1,161 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
-
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-/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
-  warnings.warn(
-/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
-
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-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 217, in <module>
-    for batch in tqdm(eval_dataloader):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/tqdm/std.py", line 1178, in __iter__
-    for obj in iterable:
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/accelerate/data_loader.py", line 394, in __iter__
-    next_batch = next(dataloader_iter)
-                 ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
-    data = self._next_data()
-           ^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 677, in _next_data
-    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/_utils/fetch.py", line 54, in fetch
-    return self.collate_fn(data)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/data/data_collator.py", line 600, in __call__
-    decoder_input_ids = self.model.prepare_decoder_input_ids_from_labels(labels=features["labels"])
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 1527, in prepare_decoder_input_ids_from_labels
-    return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 66, in shift_tokens_right
-    shifted_input_ids[:, 0] = decoder_start_token_id
-    ~~~~~~~~~~~~~~~~~^^^^^^
-IndexError: index 0 is out of bounds for dimension 1 with size 0
-
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myerrors_1564.out

@@ -1,161 +0,0 @@
-You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
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-
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-/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
-  warnings.warn(
-/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
-
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-Traceback (most recent call last):
-  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 217, in <module>
-    for batch in tqdm(eval_dataloader):
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/tqdm/std.py", line 1178, in __iter__
-    for obj in iterable:
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/accelerate/data_loader.py", line 394, in __iter__
-    next_batch = next(dataloader_iter)
-                 ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 633, in __next__
-    data = self._next_data()
-           ^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/dataloader.py", line 677, in _next_data
-    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/torch/utils/data/_utils/fetch.py", line 54, in fetch
-    return self.collate_fn(data)
-           ^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/data/data_collator.py", line 600, in __call__
-    decoder_input_ids = self.model.prepare_decoder_input_ids_from_labels(labels=features["labels"])
-                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 1527, in prepare_decoder_input_ids_from_labels
-    return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/marian/modeling_marian.py", line 66, in shift_tokens_right
-    shifted_input_ids[:, 0] = decoder_start_token_id
-    ~~~~~~~~~~~~~~~~~^^^^^^
-IndexError: index 0 is out of bounds for dimension 1 with size 0
-
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myerrors_1600.out

@@ -0,0 +1,49 @@
+You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
+
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+
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+/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
+  warnings.warn(
+/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
+Traceback (most recent call last):
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 261, in hf_raise_for_status
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/requests/models.py", line 1021, in raise_for_status
+    raise HTTPError(http_error_msg, response=self)
+requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/aatherton2024/hf_synth_trans/resolve/main/config.json
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 428, in cached_file
+    resolved_file = hf_hub_download(
+                    ^^^^^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1230, in hf_hub_download
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_validators.py", line 118, in _inner_fn
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/file_download.py", line 1606, in get_hf_file_metadata
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/huggingface_hub-0.17.1-py3.8.egg/huggingface_hub/utils/_errors.py", line 271, in hf_raise_for_status
+huggingface_hub.utils._errors.EntryNotFoundError: 404 Client Error. (Request ID: Root=1-6508f53c-403d6b2e4c215eb0090d4b33;cdf95f5b-24d2-49b8-9434-cfaa697f931b)
+
+Entry Not Found for url: https://huggingface.co/aatherton2024/hf_synth_trans/resolve/main/config.json.
+
+The above exception was the direct cause of the following exception:
+
+Traceback (most recent call last):
+  File "/mnt/storage/aatherton/hf_synth_trans/synth_translation.py", line 268, in <module>
+    translator = pipeline("translation", model=model_checkpoint)
+                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/pipelines/__init__.py", line 724, in pipeline
+    config = AutoConfig.from_pretrained(model, _from_pipeline=task, **hub_kwargs, **model_kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py", line 1007, in from_pretrained
+    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
+                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 620, in get_config_dict
+    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
+                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/configuration_utils.py", line 675, in _get_config_dict
+    resolved_config_file = cached_file(
+                           ^^^^^^^^^^^^
+  File "/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/utils/hub.py", line 479, in cached_file
+    raise EnvironmentError(
+OSError: aatherton2024/hf_synth_trans does not appear to have a file named config.json. Checkout 'https://huggingface.co/aatherton2024/hf_synth_trans/main' for available files.

myerrors_1601.out

@@ -0,0 +1,16 @@
+You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.
+
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+/mnt/storage/aatherton/anaconda3/envs/nmt/lib/python3.11/site-packages/transformers/optimization.py:411: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
+  warnings.warn(
+/mnt/storage/aatherton/hf_eng_fra_trans is already a clone of https://huggingface.co/aatherton2024/hf_eng_fra_trans. Make sure you pull the latest changes with `repo.git_pull()`.
+
+
+
+
+
+
+
+
+

myoutput_1551.out

@@ -1 +0,0 @@
-evaluate1

myoutput_1552.out

@@ -1 +0,0 @@
-evaluate1

myoutput_1553.out

@@ -1 +0,0 @@
-evaluate1

myoutput_1554.out

@@ -1 +0,0 @@
-evaluate1

myoutput_1555.out

@@ -1,5 +0,0 @@
-evaluate1
-trainer train 1
-{'loss': 1.2688, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
-{'train_runtime': 56.3764, 'train_samples_per_second': 388.035, 'train_steps_per_second': 12.133, 'train_loss': 1.1421493842587833, 'epoch': 3.0}
-evaluate 2

myoutput_1558.out

@@ -1,4 +0,0 @@
-
-
-
-evaluate1

myoutput_1559.out

@@ -1,4 +0,0 @@
-
-
-
-evaluate1

myoutput_1560.out

@@ -1,4 +0,0 @@
-
-
-
-evaluate1

myoutput_1561.out

@@ -1,8 +0,0 @@
-
-
-
-evaluate1
-trainer train 1
-{'loss': 0.6532, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
-{'train_runtime': 57.6599, 'train_samples_per_second': 379.397, 'train_steps_per_second': 11.863, 'train_loss': 0.6262621963233278, 'epoch': 3.0}
-evaluate 2

myoutput_1562.out

@@ -1,10 +0,0 @@
-
-
-
-evaluate1
-{'eval_loss': 0.5364619493484497, 'eval_bleu': 0.0, 'eval_runtime': 69.2839, 'eval_samples_per_second': 14.448, 'eval_steps_per_second': 0.231}
-trainer train 1
-{'loss': 0.4504, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
-{'train_runtime': 58.3552, 'train_samples_per_second': 374.877, 'train_steps_per_second': 11.721, 'train_loss': 0.4447354879992747, 'epoch': 3.0}
-evaluate 2
-{'eval_loss': 0.411633163690567, 'eval_bleu': 0.0, 'eval_runtime': 68.1275, 'eval_samples_per_second': 14.693, 'eval_steps_per_second': 0.235, 'epoch': 3.0}

myoutput_1563.out

@@ -1,61 +0,0 @@
-
-
-
-MarianMTModel(
-  (model): MarianModel(
-    (shared): Embedding(59514, 512, padding_idx=59513)
-    (encoder): MarianEncoder(
-      (embed_tokens): Embedding(59514, 512, padding_idx=59513)
-      (embed_positions): MarianSinusoidalPositionalEmbedding(512, 512)
-      (layers): ModuleList(
-        (0-5): 6 x MarianEncoderLayer(
-          (self_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (self_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (activation_fn): SiLUActivation()
-          (fc1): Linear(in_features=512, out_features=2048, bias=True)
-          (fc2): Linear(in_features=2048, out_features=512, bias=True)
-          (final_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-        )
-      )
-    )
-    (decoder): MarianDecoder(
-      (embed_tokens): Embedding(59514, 512, padding_idx=59513)
-      (embed_positions): MarianSinusoidalPositionalEmbedding(512, 512)
-      (layers): ModuleList(
-        (0-5): 6 x MarianDecoderLayer(
-          (self_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (activation_fn): SiLUActivation()
-          (self_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (encoder_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (encoder_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (fc1): Linear(in_features=512, out_features=2048, bias=True)
-          (fc2): Linear(in_features=2048, out_features=512, bias=True)
-          (final_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-        )
-      )
-    )
-  )
-  (lm_head): Linear(in_features=512, out_features=59514, bias=False)
-)
-evaluate1
-{'eval_loss': 0.411633163690567, 'eval_bleu': 0.0, 'eval_runtime': 69.9028, 'eval_samples_per_second': 14.32, 'eval_steps_per_second': 0.229}
-trainer train 1
-{'loss': 0.3189, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
-{'train_runtime': 57.9326, 'train_samples_per_second': 377.611, 'train_steps_per_second': 11.807, 'train_loss': 0.3294184054547583, 'epoch': 3.0}
-evaluate 2
-{'eval_loss': 0.33941635489463806, 'eval_bleu': 0.0, 'eval_runtime': 69.4586, 'eval_samples_per_second': 14.411, 'eval_steps_per_second': 0.23, 'epoch': 3.0}

myoutput_1564.out

@@ -1,61 +0,0 @@
-
-
-
-MarianMTModel(
-  (model): MarianModel(
-    (shared): Embedding(59514, 512, padding_idx=59513)
-    (encoder): MarianEncoder(
-      (embed_tokens): Embedding(59514, 512, padding_idx=59513)
-      (embed_positions): MarianSinusoidalPositionalEmbedding(512, 512)
-      (layers): ModuleList(
-        (0-5): 6 x MarianEncoderLayer(
-          (self_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (self_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (activation_fn): SiLUActivation()
-          (fc1): Linear(in_features=512, out_features=2048, bias=True)
-          (fc2): Linear(in_features=2048, out_features=512, bias=True)
-          (final_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-        )
-      )
-    )
-    (decoder): MarianDecoder(
-      (embed_tokens): Embedding(59514, 512, padding_idx=59513)
-      (embed_positions): MarianSinusoidalPositionalEmbedding(512, 512)
-      (layers): ModuleList(
-        (0-5): 6 x MarianDecoderLayer(
-          (self_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (activation_fn): SiLUActivation()
-          (self_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (encoder_attn): MarianAttention(
-            (k_proj): Linear(in_features=512, out_features=512, bias=True)
-            (v_proj): Linear(in_features=512, out_features=512, bias=True)
-            (q_proj): Linear(in_features=512, out_features=512, bias=True)
-            (out_proj): Linear(in_features=512, out_features=512, bias=True)
-          )
-          (encoder_attn_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-          (fc1): Linear(in_features=512, out_features=2048, bias=True)
-          (fc2): Linear(in_features=2048, out_features=512, bias=True)
-          (final_layer_norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
-        )
-      )
-    )
-  )
-  (lm_head): Linear(in_features=512, out_features=59514, bias=False)
-)
-evaluate1
-{'eval_loss': 0.3534283936023712, 'eval_bleu': 0.0, 'eval_runtime': 69.9139, 'eval_samples_per_second': 14.318, 'eval_steps_per_second': 0.229}
-trainer train 1
-{'loss': 0.2276, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
-{'train_runtime': 56.8014, 'train_samples_per_second': 385.131, 'train_steps_per_second': 12.042, 'train_loss': 0.2556379162080107, 'epoch': 3.0}
-evaluate 2
-{'eval_loss': 0.30410629510879517, 'eval_bleu': 0.0, 'eval_runtime': 69.9679, 'eval_samples_per_second': 14.307, 'eval_steps_per_second': 0.229, 'epoch': 3.0}

myoutput_1600.out

@@ -0,0 +1,8 @@
+evaluate1
+{'eval_loss': 0.3294467329978943, 'eval_bleu': 0.021732338702567133, 'eval_chrf': 24.996195060769814, 'eval_runtime': 70.6427, 'eval_samples_per_second': 14.17, 'eval_steps_per_second': 0.226}
+trainer train 1
+{'loss': 0.2145, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
+{'train_runtime': 56.8334, 'train_samples_per_second': 384.914, 'train_steps_per_second': 12.035, 'train_loss': 0.2377676657068799, 'epoch': 3.0}
+evaluate 2
+{'eval_loss': 0.2867695093154907, 'eval_bleu': 0.02226070832187467, 'eval_chrf': 25.804707746098266, 'eval_runtime': 69.9013, 'eval_samples_per_second': 14.32, 'eval_steps_per_second': 0.229, 'epoch': 3.0}
+training model now

myoutput_1601.out

@@ -0,0 +1,9 @@
+evaluate1
+{'eval_loss': 0.2867695093154907, 'eval_bleu': 0.02226070832187467, 'eval_chrf': 25.804707746098266, 'eval_runtime': 73.0567, 'eval_samples_per_second': 13.702, 'eval_steps_per_second': 0.219}
+trainer train 1
+{'loss': 0.1428, 'learning_rate': 5.380116959064328e-06, 'epoch': 2.19}
+{'train_runtime': 57.3032, 'train_samples_per_second': 381.759, 'train_steps_per_second': 11.936, 'train_loss': 0.17679918300338657, 'epoch': 3.0}
+evaluate 2
+{'eval_loss': 0.26398155093193054, 'eval_bleu': 0.02310668515912661, 'eval_chrf': 26.48909190811468, 'eval_runtime': 71.4593, 'eval_samples_per_second': 14.008, 'eval_steps_per_second': 0.224, 'epoch': 3.0}
+training model now
+[{'translation_text': 'axinquigudiflogaqueh.aqueh.aqueh.aqueh.aqueh.aqueh.aqueh.aqueh.aqueh.aquaqueh.aqueh.aqueh.aqueh.ah.ah.ah.ah.ac.ah.ac.aquac.aquac.aquaquaquaquaqabah.aqabac.aquaquaquaqababac.ac.ac.ac.ac.ac.aquac.ac.aquac.ac.aquac.caquac.ac.aqac.aqacbaqacbac.aqacaquaqaqubach.aqaqach.aqaqaquhaqaqachbquhbquququququququmabquhaquhaquququququququququququququququmababababababququququququququmabababachbachbachbacqubachchbachbobobachchchchchchchchchchchchchchchchchchchchchchchchbohbohbohdugogogogohgogogogogogogogogogogogogogogogogo'}]

output/added_tokens.json

@@ -0,0 +1,3 @@
+{
+  "[PAD]": 259
+}

output/config.json

@@ -0,0 +1,62 @@
+{
+  "_name_or_path": "eng-nah-svo-translation",
+  "_num_labels": 3,
+  "activation_dropout": 0.0,
+  "activation_function": "swish",
+  "add_bias_logits": false,
+  "add_final_layer_norm": false,
+  "architectures": [
+    "MarianMTModel"
+  ],
+  "attention_dropout": 0.0,
+  "bad_words_ids": [
+    [
+      59513
+    ]
+  ],
+  "bos_token_id": 0,
+  "classif_dropout": 0.0,
+  "classifier_dropout": 0.0,
+  "d_model": 512,
+  "decoder_attention_heads": 8,
+  "decoder_ffn_dim": 2048,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 6,
+  "decoder_start_token_id": 59513,
+  "decoder_vocab_size": 59514,
+  "dropout": 0.1,
+  "encoder_attention_heads": 8,
+  "encoder_ffn_dim": 2048,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 6,
+  "eos_token_id": 0,
+  "forced_eos_token_id": 0,
+  "gradient_checkpointing": false,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "max_length": 512,
+  "max_position_embeddings": 512,
+  "model_type": "marian",
+  "normalize_before": false,
+  "normalize_embedding": false,
+  "num_beams": 4,
+  "num_hidden_layers": 6,
+  "pad_token_id": 59513,
+  "scale_embedding": true,
+  "share_encoder_decoder_embeddings": true,
+  "static_position_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 59514
+}

output/generation_config.json

@@ -0,0 +1,16 @@
+{
+  "bad_words_ids": [
+    [
+      59513
+    ]
+  ],
+  "bos_token_id": 0,
+  "decoder_start_token_id": 59513,
+  "eos_token_id": 0,
+  "forced_eos_token_id": 0,
+  "max_length": 512,
+  "num_beams": 4,
+  "pad_token_id": 59513,
+  "renormalize_logits": true,
+  "transformers_version": "4.32.1"
+}