Training

README.md

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+---
+license: apache-2.0
+base_model: IlyaGusev/rut5_base_sum_gazeta
+tags:
+- summarization_2
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: rut5_base_sum_gazeta-finetuned
+  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. -->
+
+# rut5_base_sum_gazeta-finetuned
+
+This model is a fine-tuned version of [IlyaGusev/rut5_base_sum_gazeta](https://huggingface.co/IlyaGusev/rut5_base_sum_gazeta) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.1124
+- Rouge1: 0.0
+- Rouge2: 0.0
+- Rougel: 0.0
+- Rougelsum: 0.0
+
+## 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: 5.6e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 2.9877        | 1.0   | 12   | 2.3994          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 2.5964        | 2.0   | 24   | 2.2629          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 2.3873        | 3.0   | 36   | 2.2001          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 2.2627        | 4.0   | 48   | 2.1574          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 2.1536        | 5.0   | 60   | 2.1319          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 2.0937        | 6.0   | 72   | 2.1214          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 1.9039        | 7.0   | 84   | 2.1149          | 0.0    | 0.0    | 0.0    | 0.0       |
+| 1.9739        | 8.0   | 96   | 2.1124          | 0.0    | 0.0    | 0.0    | 0.0       |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "IlyaGusev/rut5_base_sum_gazeta",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "bos_token_id": 2,
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 2,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "max_length": 200,
+  "model_type": "t5",
+  "num_beams": 5,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.0",
+  "use_cache": true,
+  "vocab_size": 30000
+}

generation_config.json

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+{
+  "bos_token_id": 2,
+  "decoder_start_token_id": 2,
+  "eos_token_id": 1,
+  "max_length": 200,
+  "num_beams": 5,
+  "pad_token_id": 0,
+  "transformers_version": "4.33.0"
+}

pytorch_model.bin

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special_tokens_map.json

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+  "eos_token": "</s>",
+  "pad_token": "<pad>",
+  "unk_token": "<unk>"
+}

spiece.model

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tokenizer_config.json

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+{
+  "additional_special_tokens": null,
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "</s>",
+  "extra_ids": 0,
+  "max_length": 200,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "stride": 0,
+  "tokenizer_class": "T5Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}

training_args.bin

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