End of training

README.md

@@ -0,0 +1,72 @@
+---
+license: mit
+base_model: naver-clova-ix/donut-base
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+- wer
+model-index:
+- name: donut_experiment_bayesian_trial_13
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# donut_experiment_bayesian_trial_13
+
+This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5500
+- Bleu: 0.0682
+- Precisions: [0.8219461697722568, 0.755868544600939, 0.7073170731707317, 0.6474358974358975]
+- Brevity Penalty: 0.0934
+- Length Ratio: 0.2967
+- Translation Length: 483
+- Reference Length: 1628
+- Cer: 0.7531
+- Wer: 0.8285
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 6.0814226870239416e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Bleu   | Precisions                                                                       | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer    | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
+| 0.0455        | 1.0   | 253  | 0.5262          | 0.0660 | [0.8166666666666667, 0.7446808510638298, 0.6939890710382514, 0.6407766990291263] | 0.0915          | 0.2948       | 480                | 1628             | 0.7601 | 0.8316 |
+| 0.0276        | 2.0   | 506  | 0.5500          | 0.0682 | [0.8219461697722568, 0.755868544600939, 0.7073170731707317, 0.6474358974358975]  | 0.0934          | 0.2967       | 483                | 1628             | 0.7531 | 0.8285 |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.1.0
+- Datasets 2.18.0
+- Tokenizers 0.19.1

added_tokens.json

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+  "</s_company>": 57530,
+  "</s_date>": 57528,
+  "</s_total>": 57526,
+  "<s_address>": 57531,
+  "<s_company>": 57529,
+  "<s_date>": 57527,
+  "<s_iitcdip>": 57523,
+  "<s_synthdog>": 57524,
+  "<s_total>": 57525,
+  "<sep/>": 57522
+}

generation_config.json

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+{
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "pad_token_id": 1,
+  "transformers_version": "4.40.0"
+}

model.safetensors

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 size 809103512

preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_thumbnail",
+    "do_align_long_axis",
+    "do_pad",
+    "random_padding",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "do_align_long_axis": false,
+  "do_normalize": true,
+  "do_pad": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "do_thumbnail": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "DonutImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "processor_class": "DonutProcessor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": [
+    720,
+    960
+  ]
+}

sentencepiece.bpe.model

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+size 1296245

special_tokens_map.json

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+}

tokenizer_config.json

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+}