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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: t5-small-ret-conceptnet2 |
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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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# t5-small-ret-conceptnet2 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1709 |
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- Acc: {'accuracy': 0.8700980392156863} |
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- Precision: {'precision': 0.811340206185567} |
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- Recall: {'recall': 0.9644607843137255} |
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- F1: {'f1': 0.8812989921612542} |
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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: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Acc | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------------:|:------------------------------:|:--------------------------:| |
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| 0.1989 | 1.0 | 721 | 0.1709 | {'accuracy': 0.8700980392156863} | {'precision': 0.811340206185567} | {'recall': 0.9644607843137255} | {'f1': 0.8812989921612542} | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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