End of training

README.md

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+---
+license: apache-2.0
+base_model: google/mt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mT5-TextSimp-LT-BatchSize8-lr5e-5
+  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-TextSimp-LT-BatchSize8-lr5e-5
+
+This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0969
+- Rouge1: 0.6185
+- Rouge2: 0.4427
+- Rougel: 0.6087
+- Gen Len: 38.0501
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
+| 32.3498       | 0.96  | 200  | 26.0719         | 0.0008 | 0.0    | 0.0008 | 512.0   |
+| 5.8297        | 1.91  | 400  | 4.1306          | 0.0059 | 0.0    | 0.0058 | 45.0573 |
+| 0.7087        | 2.87  | 600  | 0.6039          | 0.003  | 0.0    | 0.0029 | 39.0501 |
+| 0.4166        | 3.83  | 800  | 0.1958          | 0.3954 | 0.2416 | 0.3823 | 39.0501 |
+| 0.2193        | 4.78  | 1000 | 0.1172          | 0.5244 | 0.3536 | 0.514  | 38.0501 |
+| 0.1371        | 5.74  | 1200 | 0.1029          | 0.5936 | 0.4122 | 0.5839 | 38.0501 |
+| 0.1971        | 6.7   | 1400 | 0.0974          | 0.6077 | 0.4302 | 0.5984 | 38.0501 |
+| 0.1653        | 7.66  | 1600 | 0.0969          | 0.6185 | 0.4427 | 0.6087 | 38.0501 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.1
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "google/mt5-base",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "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": "t5",
+  "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": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 250112
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.36.2"
+}

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special_tokens_map.json

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spiece.model

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tokenizer_config.json

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+  "tokenizer_class": "T5Tokenizer",
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+}

training_args.bin

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