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--- |
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library_name: transformers |
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base_model: t-tech/T-lite-it-1.0 |
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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: T-lite-it-1.0-pseudo-base |
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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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# t-lite_part1-2_lr1e4_wsd_bs128 |
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This model is a fine-tuned version of [t-tech/T-lite-it-1.0](https://huggingface.co/t-tech/T-lite-it-1.0) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3980 |
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- Accuracy: 0.6669 |
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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: 0.0001 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: warmup_stable_decay |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 0.5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| No log | 0.0001 | 1 | 1.4751 | 0.6606 | |
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| 1.5071 | 0.0354 | 500 | 1.4113 | 0.6647 | |
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| 1.5003 | 0.0709 | 1000 | 1.4080 | 0.6649 | |
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| 1.4959 | 0.1063 | 1500 | 1.4063 | 0.6654 | |
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| 1.5019 | 0.1418 | 2000 | 1.4054 | 0.6655 | |
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| 1.4891 | 0.1772 | 2500 | 1.4047 | 0.6656 | |
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| 1.4916 | 0.2126 | 3000 | 1.4040 | 0.6657 | |
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| 1.496 | 0.2481 | 3500 | 1.4034 | 0.6657 | |
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| 1.495 | 0.2835 | 4000 | 1.4032 | 0.6657 | |
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| 1.4934 | 0.3189 | 4500 | 1.4030 | 0.6658 | |
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| 1.4849 | 0.3544 | 5000 | 1.4029 | 0.6660 | |
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| 1.4833 | 0.3898 | 5500 | 1.4024 | 0.6661 | |
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| 1.4909 | 0.4253 | 6000 | 1.4023 | 0.6661 | |
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| 1.4923 | 0.4607 | 6500 | 1.4000 | 0.6665 | |
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| 1.4965 | 0.4961 | 7000 | 1.3979 | 0.6669 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04 |
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- Datasets 2.18.0 |
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- Tokenizers 0.20.3 |
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