End of training

README.md

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+---
+license: apache-2.0
+base_model: google/mt5-large
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: MT5-large_NO-idun-20epoch
+  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-large_NO-idun-20epoch
+
+This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6704
+- Rouge1: 41.2841
+- Rouge2: 17.1062
+- Rougel: 27.4493
+- Rougelsum: 37.2798
+- Gen Len: 113.9043
+
+## 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: 5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
+| No log        | 0.98  | 46   | 6.3605          | 26.7151 | 6.6971  | 17.105  | 23.7109   | 127.0    |
+| No log        | 1.99  | 93   | 4.7689          | 32.3429 | 12.2149 | 20.2642 | 28.985    | 127.0    |
+| No log        | 2.99  | 140  | 1.8494          | 37.8255 | 14.0518 | 22.4306 | 33.4714   | 124.9255 |
+| No log        | 4.0   | 187  | 1.7294          | 39.5672 | 16.4066 | 24.4606 | 35.4055   | 121.1702 |
+| No log        | 4.98  | 233  | 1.6796          | 39.5901 | 16.6044 | 25.6316 | 35.5093   | 120.5532 |
+| No log        | 5.99  | 280  | 1.6557          | 39.8141 | 15.6699 | 24.8691 | 36.0578   | 123.5745 |
+| No log        | 6.99  | 327  | 1.6525          | 40.0304 | 16.6229 | 25.7054 | 36.3012   | 121.0638 |
+| No log        | 8.0   | 374  | 1.6484          | 40.5564 | 16.0763 | 26.0131 | 36.1736   | 119.8936 |
+| No log        | 8.98  | 420  | 1.6499          | 39.9522 | 16.6648 | 26.419  | 35.9155   | 118.9468 |
+| No log        | 9.99  | 467  | 1.6494          | 41.0085 | 17.1259 | 27.041  | 36.9109   | 115.8085 |
+| 3.1043        | 10.99 | 514  | 1.6485          | 41.5339 | 17.5085 | 27.6923 | 37.2051   | 115.8936 |
+| 3.1043        | 12.0  | 561  | 1.6488          | 40.3393 | 16.453  | 26.8152 | 36.3384   | 113.4787 |
+| 3.1043        | 12.98 | 607  | 1.6485          | 42.0494 | 17.8355 | 27.9197 | 37.9283   | 115.8617 |
+| 3.1043        | 13.99 | 654  | 1.6533          | 40.7634 | 16.8655 | 26.8984 | 36.5803   | 114.6809 |
+| 3.1043        | 14.99 | 701  | 1.6570          | 41.6789 | 17.5072 | 27.7933 | 37.4503   | 114.1596 |
+| 3.1043        | 16.0  | 748  | 1.6594          | 41.5489 | 17.2787 | 27.7975 | 37.2948   | 113.7447 |
+| 3.1043        | 16.98 | 794  | 1.6643          | 41.3929 | 17.0913 | 27.4552 | 37.2221   | 113.3936 |
+| 3.1043        | 17.99 | 841  | 1.6658          | 41.4336 | 16.9364 | 27.4426 | 37.1709   | 113.1915 |
+| 3.1043        | 18.99 | 888  | 1.6699          | 41.5935 | 17.1928 | 27.2885 | 37.2653   | 113.6170 |
+| 3.1043        | 19.68 | 920  | 1.6704          | 41.2841 | 17.1062 | 27.4493 | 37.2798   | 113.9043 |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

config.json

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+{
+  "_name_or_path": "google/mt5-large",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2816,
+  "d_kv": 64,
+  "d_model": 1024,
+  "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,
+  "length_penalty": 2.0,
+  "max_length": 128,
+  "model_type": "mt5",
+  "no_repeat_ngram_size": 3,
+  "num_beams": 4,
+  "num_decoder_layers": 24,
+  "num_heads": 16,
+  "num_layers": 24,
+  "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": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 250112
+}

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "length_penalty": 2.0,
+  "max_length": 128,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 4,
+  "pad_token_id": 0,
+  "transformers_version": "4.32.1"
+}

pytorch_model.bin

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special_tokens_map.json

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+  "pad_token": "<pad>",
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+}

spiece.model

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": true,
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+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "T5Tokenizer",
+  "tokenizer_file": null,
+  "unk_token": "<unk>"
+}

training_args.bin

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