End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: muchad/idt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+model-index:
+- name: idt5-base-mcqg-RACE-id
+  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. -->
+
+# idt5-base-mcqg-RACE-id
+
+This model is a fine-tuned version of [muchad/idt5-base](https://huggingface.co/muchad/idt5-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1419
+- Rouge1: 0.3828
+- Rouge2: 0.2464
+- Rougel: 0.3635
+- Rougelsum: 0.3687
+- Bleu: 0.2053
+- Rouge All: {'rouge1': 0.38280297280337106, 'rouge2': 0.2463717712635165, 'rougeL': 0.36348416422814667, 'rougeLsum': 0.3686870784292893}
+- Bleu All: {'bleu': 0.20529625464163276, 'precisions': [0.544206419519389, 0.4080415448721935, 0.3448035357165733, 0.29241227961620014], 'brevity_penalty': 0.5307282267142313, 'length_ratio': 0.6121804805088057, 'translation_length': 181727, 'reference_length': 296852}
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu   | Rouge All                                                                                                                      | Bleu All                                                                                                                                                                                                                                                             |
+|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 1.5379        | 1.0   | 36284  | 1.2265          | 0.3371 | 0.2094 | 0.3205 | 0.3253    | 0.1983 | {'rouge1': 0.33711648528419197, 'rouge2': 0.20935180236052028, 'rougeL': 0.3205203116477598, 'rougeLsum': 0.32529545761604484} | {'bleu': 0.19831282890007307, 'precisions': [0.5217314036276394, 0.3946142969363708, 0.33979358871868, 0.29601867266779885], 'brevity_penalty': 0.5227719650702349, 'length_ratio': 0.6065716249174673, 'translation_length': 180062, 'reference_length': 296852}    |
+| 1.3644        | 2.0   | 72568  | 1.1698          | 0.3630 | 0.2295 | 0.3447 | 0.3498    | 0.2039 | {'rouge1': 0.3629660167163082, 'rouge2': 0.2295266351540305, 'rougeL': 0.3446608461843371, 'rougeLsum': 0.34976374071944816}   | {'bleu': 0.20392626154873386, 'precisions': [0.5382410077317733, 0.4070086261940831, 0.3470977823014178, 0.2976925955182306], 'brevity_penalty': 0.52574250563914, 'length_ratio': 0.6086635764623449, 'translation_length': 180683, 'reference_length': 296852}     |
+| 1.2742        | 3.0   | 108852 | 1.1465          | 0.3728 | 0.2366 | 0.3537 | 0.3587    | 0.2035 | {'rouge1': 0.3728293856857868, 'rouge2': 0.2365878815089809, 'rougeL': 0.35374960442490494, 'rougeLsum': 0.3587096713960251}   | {'bleu': 0.20345989395248457, 'precisions': [0.5398174482439315, 0.40446504788430504, 0.34243731944791184, 0.2920075779511404], 'brevity_penalty': 0.5293013871683313, 'length_ratio': 0.6111732445797906, 'translation_length': 181428, 'reference_length': 296852} |
+| 1.1868        | 4.0   | 145136 | 1.1392          | 0.3788 | 0.2418 | 0.3597 | 0.3647    | 0.2045 | {'rouge1': 0.37877643387013765, 'rouge2': 0.2417733244099297, 'rougeL': 0.35970895267024183, 'rougeLsum': 0.3646545306105341}  | {'bleu': 0.20448179885293769, 'precisions': [0.5452928078502008, 0.4092357483817759, 0.34584093592358056, 0.2932385759829968], 'brevity_penalty': 0.5272049129237822, 'length_ratio': 0.6096943931656179, 'translation_length': 180989, 'reference_length': 296852}  |
+| 1.1429        | 5.0   | 181420 | 1.1419          | 0.3828 | 0.2464 | 0.3635 | 0.3687    | 0.2053 | {'rouge1': 0.38280297280337106, 'rouge2': 0.2463717712635165, 'rougeL': 0.36348416422814667, 'rougeLsum': 0.3686870784292893}  | {'bleu': 0.20529625464163276, 'precisions': [0.544206419519389, 0.4080415448721935, 0.3448035357165733, 0.29241227961620014], 'brevity_penalty': 0.5307282267142313, 'length_ratio': 0.6121804805088057, 'translation_length': 181727, 'reference_length': 296852}   |
+
+
+### Framework versions
+
+- Transformers 4.56.2
+- Pytorch 2.8.0+cu129
+- Datasets 4.2.0
+- Tokenizers 0.22.1

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": [
+    1
+  ],
+  "pad_token_id": 0,
+  "transformers_version": "4.56.2"
+}