End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/mt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: mt5-rouge-durga-q1-clean
+  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-rouge-durga-q1-clean
+
+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: 1.7819
+- Rouge1: 0.3074
+- Rouge2: 0.0953
+- Rougel: 0.3026
+- Rougelsum: 0.3008
+
+## 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: 0.0003
+- train_batch_size: 20
+- eval_batch_size: 20
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 15.8442       | 1.0   | 3    | 11.1246         | 0.0148 | 0.0015 | 0.0152 | 0.0151    |
+| 13.0661       | 2.0   | 6    | 9.3553          | 0.0226 | 0.0052 | 0.0219 | 0.0217    |
+| 11.7048       | 3.0   | 9    | 8.0317          | 0.0198 | 0.0029 | 0.0177 | 0.0190    |
+| 8.87          | 4.0   | 12   | 7.1382          | 0.0461 | 0.0105 | 0.0423 | 0.0406    |
+| 11.0893       | 5.0   | 15   | 6.7905          | 0.0611 | 0.0106 | 0.0512 | 0.0503    |
+| 9.8787        | 6.0   | 18   | 6.5255          | 0.0900 | 0.0224 | 0.0800 | 0.0782    |
+| 9.8189        | 7.0   | 21   | 6.7007          | 0.0944 | 0.0231 | 0.0876 | 0.0861    |
+| 8.2022        | 8.0   | 24   | 6.2109          | 0.0953 | 0.0227 | 0.0899 | 0.0910    |
+| 8.5899        | 9.0   | 27   | 5.9520          | 0.0965 | 0.0171 | 0.0897 | 0.0914    |
+| 7.5305        | 10.0  | 30   | 5.5748          | 0.0855 | 0.0157 | 0.0841 | 0.0821    |
+| 7.0381        | 11.0  | 33   | 5.2219          | 0.0622 | 0.0095 | 0.0592 | 0.0585    |
+| 6.675         | 12.0  | 36   | 4.8006          | 0.0529 | 0.0048 | 0.0499 | 0.0489    |
+| 7.4134        | 13.0  | 39   | 4.3795          | 0.0693 | 0.0079 | 0.0635 | 0.0610    |
+| 5.8722        | 14.0  | 42   | 3.9322          | 0.1060 | 0.0128 | 0.1003 | 0.1009    |
+| 4.5875        | 15.0  | 45   | 3.5017          | 0.1012 | 0.0069 | 0.0968 | 0.0968    |
+| 5.3675        | 16.0  | 48   | 3.1927          | 0.0944 | 0.0020 | 0.0915 | 0.0913    |
+| 4.2999        | 17.0  | 51   | 2.8956          | 0.0890 | 0.0091 | 0.0831 | 0.0849    |
+| 4.3349        | 18.0  | 54   | 2.7138          | 0.1164 | 0.0074 | 0.1114 | 0.1128    |
+| 3.9688        | 19.0  | 57   | 2.5350          | 0.1122 | 0.0    | 0.1122 | 0.1121    |
+| 4.2931        | 20.0  | 60   | 2.4138          | 0.1122 | 0.0    | 0.1122 | 0.1121    |
+| 3.8427        | 21.0  | 63   | 2.3127          | 0.1122 | 0.0    | 0.1122 | 0.1121    |
+| 3.2991        | 22.0  | 66   | 2.2054          | 0.1122 | 0.0    | 0.1122 | 0.1121    |
+| 3.1351        | 23.0  | 69   | 2.1069          | 0.1122 | 0.0    | 0.1122 | 0.1121    |
+| 3.023         | 24.0  | 72   | 2.0208          | 0.1142 | 0.0    | 0.1140 | 0.1139    |
+| 3.4366        | 25.0  | 75   | 1.9500          | 0.1793 | 0.0352 | 0.1713 | 0.1711    |
+| 2.7941        | 26.0  | 78   | 1.9068          | 0.3104 | 0.0909 | 0.3016 | 0.3005    |
+| 2.9454        | 27.0  | 81   | 1.8419          | 0.3086 | 0.0940 | 0.3009 | 0.2984    |
+| 2.6117        | 28.0  | 84   | 1.8775          | 0.3135 | 0.0955 | 0.3086 | 0.3067    |
+| 2.6785        | 29.0  | 87   | 1.7772          | 0.3020 | 0.0946 | 0.2987 | 0.2968    |
+| 2.7523        | 30.0  | 90   | 1.7819          | 0.3074 | 0.0953 | 0.3026 | 0.3008    |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.5.0+cu121
+- Datasets 3.0.2
+- Tokenizers 0.20.1

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": "4.46.1",
+  "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": "4.46.1"
+}

model.safetensors

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special_tokens_map.json

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+{
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

spiece.model

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tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  "additional_special_tokens": [],
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "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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