End of training

README.md

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+---
+license: apache-2.0
+base_model: google/mt5-small
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mt5-small-finetuned-b8-e10-1024-128
+  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. -->
+
+# mt5-small-finetuned-b8-e10-1024-128
+
+This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.3822
+- Rouge1: 13.327
+- Rouge2: 4.8244
+- Rougel: 13.1978
+- Rougelsum: 13.2133
+- Gen Len: 17.5592
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 4.7372        | 1.0   | 1357  | 3.8287          | 9.3951  | 3.6576 | 9.342   | 9.3047    | 12.6653 |
+| 4.3162        | 2.0   | 2714  | 3.6750          | 10.9224 | 4.1119 | 10.8209 | 10.8235   | 15.0997 |
+| 4.1726        | 3.0   | 4071  | 3.5668          | 11.7438 | 4.2353 | 11.6204 | 11.6087   | 16.5169 |
+| 4.0439        | 4.0   | 5428  | 3.5002          | 12.402  | 4.4267 | 12.2785 | 12.2924   | 17.0402 |
+| 3.9978        | 5.0   | 6785  | 3.4494          | 12.7762 | 4.5509 | 12.6699 | 12.6829   | 17.2466 |
+| 3.9687        | 6.0   | 8142  | 3.4229          | 12.9652 | 4.6727 | 12.8555 | 12.8761   | 17.4303 |
+| 3.8639        | 7.0   | 9499  | 3.4058          | 13.4216 | 4.784  | 13.3097 | 13.2988   | 17.4252 |
+| 3.8474        | 8.0   | 10856 | 3.3924          | 13.2422 | 4.7672 | 13.1416 | 13.12     | 17.5046 |
+| 3.843         | 9.0   | 12213 | 3.3845          | 13.2519 | 4.8713 | 13.1421 | 13.1304   | 17.5371 |
+| 3.8545        | 10.0  | 13570 | 3.3822          | 13.327  | 4.8244 | 13.1978 | 13.2133   | 17.5592 |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.14.6
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "google/mt5-small",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 1024,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "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,
+  "model_type": "mt5",
+  "num_decoder_layers": 8,
+  "num_heads": 6,
+  "num_layers": 8,
+  "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": 250112
+}

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "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,
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+  "extra_ids": 0,
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "T5Tokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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