End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,71 @@
+---
+license: apache-2.0
+base_model: google/mt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+model-index:
+- name: mt5-base-lit-simplif
+  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-base-lit-simplif
+
+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: 1.1660
+- Rouge1: 45.9067
+- Rouge2: 33.3486
+- Rougel: 43.6217
+- Rougelsum: 43.7128
+- Gen Len: 17.3389
+- Bleu: 11.5761
+- Corpus Bleu: 8.3337
+
+## 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
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Bleu    | Corpus Bleu |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-----------:|
+| No log        | 1.0   | 209  | 1.7570          | 22.6673 | 14.3228 | 21.6876 | 21.634    | 11.9379 | 4.355   | 5.0525      |
+| No log        | 2.0   | 418  | 1.3636          | 40.2937 | 28.0627 | 38.6255 | 38.8148   | 16.9737 | 10.3859 | 8.7596      |
+| 4.4247        | 3.0   | 627  | 1.2516          | 40.7671 | 28.2819 | 38.4458 | 38.598    | 18.0692 | 8.7679  | 8.1542      |
+| 4.4247        | 4.0   | 836  | 1.1865          | 45.1478 | 32.7329 | 42.788  | 42.9494   | 17.4988 | 11.2435 | 8.2933      |
+| 1.7397        | 5.0   | 1045 | 1.1660          | 45.9067 | 33.3486 | 43.6217 | 43.7128   | 17.3389 | 11.5761 | 8.3337      |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.1.1
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "google/mt5-base",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "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": "mt5",
+  "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": 250112
+}

generation_config.json

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+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.33.0"
+}

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special_tokens_map.json

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tokenizer_config.json

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