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--- |
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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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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-amazon-en-es |
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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-finetuned-amazon-en-es |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0609 |
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- Rouge1: 35.0709 |
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- Rouge2: 16.7086 |
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- Rougel: 34.3217 |
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- Rougelsum: 34.3182 |
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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: 5.6e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| No log | 1.0 | 1209 | 3.3452 | 28.1494 | 11.5385 | 27.8138 | 27.9215 | |
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| 5.3779 | 2.0 | 2418 | 3.2066 | 29.2799 | 14.9292 | 28.3282 | 28.4643 | |
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| 5.3779 | 3.0 | 3627 | 3.1105 | 31.9146 | 15.8212 | 31.0157 | 30.9702 | |
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| 3.5145 | 4.0 | 4836 | 3.0808 | 32.6703 | 15.9624 | 31.568 | 31.5303 | |
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| 3.5145 | 5.0 | 6045 | 3.0837 | 33.8454 | 16.3402 | 32.6727 | 32.8738 | |
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| 3.2939 | 6.0 | 7254 | 3.0655 | 32.4588 | 15.713 | 31.7059 | 31.7646 | |
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| 3.2939 | 7.0 | 8463 | 3.0576 | 34.764 | 16.6023 | 34.1524 | 34.0333 | |
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| 3.2076 | 8.0 | 9672 | 3.0609 | 35.0709 | 16.7086 | 34.3217 | 34.3182 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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