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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: mt5-small-gigatrue-layercut-D456 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mt5-small-gigatrue-layercut-D456 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6214 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 4.249 | 0.1015 | 3000 | 2.7814 | |
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| 3.4936 | 0.2030 | 6000 | 2.7083 | |
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| 3.4312 | 0.3044 | 9000 | 2.6841 | |
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| 3.4015 | 0.4059 | 12000 | 2.6656 | |
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| 3.3795 | 0.5074 | 15000 | 2.6510 | |
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| 3.3716 | 0.6089 | 18000 | 2.6407 | |
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| 3.3644 | 0.7104 | 21000 | 2.6435 | |
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| 3.3595 | 0.8119 | 24000 | 2.6354 | |
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| 3.3534 | 0.9133 | 27000 | 2.6312 | |
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| 3.3522 | 1.0148 | 30000 | 2.6333 | |
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| 3.3501 | 1.1163 | 33000 | 2.6283 | |
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| 3.3451 | 1.2178 | 36000 | 2.6231 | |
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| 3.344 | 1.3193 | 39000 | 2.6240 | |
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| 3.3423 | 1.4207 | 42000 | 2.6217 | |
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| 3.3419 | 1.5222 | 45000 | 2.6252 | |
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| 3.3366 | 1.6237 | 48000 | 2.6247 | |
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| 3.3399 | 1.7252 | 51000 | 2.6215 | |
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| 3.3344 | 1.8267 | 54000 | 2.6219 | |
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| 3.337 | 1.9282 | 57000 | 2.6212 | |
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| 3.3394 | 2.0296 | 60000 | 2.6211 | |
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| 3.3393 | 2.1311 | 63000 | 2.6212 | |
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| 3.3353 | 2.2326 | 66000 | 2.6227 | |
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| 3.3369 | 2.3341 | 69000 | 2.6227 | |
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| 3.3348 | 2.4356 | 72000 | 2.6220 | |
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| 3.3358 | 2.5370 | 75000 | 2.6211 | |
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| 3.3377 | 2.6385 | 78000 | 2.6211 | |
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| 3.3336 | 2.7400 | 81000 | 2.6218 | |
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| 3.3359 | 2.8415 | 84000 | 2.6216 | |
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| 3.3368 | 2.9430 | 87000 | 2.6214 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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