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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/long-t5-tglobal-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_smollm2_1.7b |
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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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# jackmedda/google-long-t5-tglobal-base_finetuned_augmented_augmented_smollm2_1.7b |
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This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5509 |
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- Accuracy: 0.7647 |
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- F1: 0.8667 |
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- Precision: 0.7647 |
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- Recall: 1.0 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5448 | 1.0 | 92 | 0.6180 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.2297 | 2.0 | 184 | 0.8274 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.9201 | 3.0 | 276 | 1.2538 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 1.2834 | 4.0 | 368 | 1.4504 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.6816 | 5.0 | 460 | 1.5083 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.679 | 6.0 | 552 | 1.5801 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.7355 | 7.0 | 644 | 1.5833 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.4686 | 8.0 | 736 | 1.5327 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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| 0.4904 | 9.0 | 828 | 1.4804 | 0.7 | 0.8235 | 0.7 | 1.0 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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