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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-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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model-index: |
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- name: t5_base_twitter |
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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_base_twitter |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4913 |
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- Accuracy: 0.7656 |
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- F1 Macro: 0.7266 |
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- F1 Micro: 0.7656 |
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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: 0.0005 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 0.4808 | 0.18 | 50 | 0.5170 | 0.7445 | 0.6740 | 0.7445 | |
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| 0.5169 | 0.37 | 100 | 0.5100 | 0.7555 | 0.7269 | 0.7555 | |
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| 0.4548 | 0.55 | 150 | 0.4922 | 0.7647 | 0.7017 | 0.7647 | |
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| 0.498 | 0.74 | 200 | 0.5057 | 0.7518 | 0.6776 | 0.7518 | |
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| 0.4844 | 0.92 | 250 | 0.4913 | 0.7656 | 0.7266 | 0.7656 | |
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| 0.3949 | 1.1 | 300 | 0.5401 | 0.7482 | 0.6885 | 0.7482 | |
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| 0.4028 | 1.29 | 350 | 0.5463 | 0.7482 | 0.7209 | 0.7482 | |
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| 0.3778 | 1.47 | 400 | 0.5438 | 0.7555 | 0.7087 | 0.7555 | |
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| 0.4383 | 1.65 | 450 | 0.5412 | 0.7381 | 0.7095 | 0.7381 | |
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| 0.3984 | 1.84 | 500 | 0.5293 | 0.7555 | 0.7239 | 0.7555 | |
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| 0.3122 | 2.02 | 550 | 0.5272 | 0.7564 | 0.7212 | 0.7564 | |
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| 0.2764 | 2.21 | 600 | 0.5961 | 0.7463 | 0.7048 | 0.7463 | |
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| 0.236 | 2.39 | 650 | 0.6630 | 0.7454 | 0.6996 | 0.7454 | |
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| 0.1996 | 2.57 | 700 | 0.7070 | 0.7482 | 0.6967 | 0.7482 | |
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| 0.2245 | 2.76 | 750 | 0.6734 | 0.7454 | 0.7016 | 0.7454 | |
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| 0.2903 | 2.94 | 800 | 0.6760 | 0.7454 | 0.6954 | 0.7454 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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