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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: falcon-7b-ft-self_instruct |
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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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# falcon-7b-ft-self_instruct |
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This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharded-bf16) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7991 |
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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: 0.0002 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9935 | 0.09 | 100 | 1.0028 | |
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| 1.0094 | 0.17 | 200 | 0.9614 | |
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| 0.8897 | 0.26 | 300 | 0.9396 | |
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| 0.9435 | 0.34 | 400 | 0.9260 | |
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| 0.9618 | 0.43 | 500 | 0.9146 | |
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| 0.8103 | 0.52 | 600 | 0.9035 | |
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| 0.8889 | 0.6 | 700 | 0.8966 | |
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| 0.8915 | 0.69 | 800 | 0.8884 | |
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| 0.8814 | 0.77 | 900 | 0.8833 | |
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| 0.9207 | 0.86 | 1000 | 0.8742 | |
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| 0.8284 | 0.95 | 1100 | 0.8693 | |
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| 0.8283 | 1.03 | 1200 | 0.8682 | |
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| 0.7445 | 1.12 | 1300 | 0.8659 | |
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| 0.8238 | 1.2 | 1400 | 0.8640 | |
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| 0.7448 | 1.29 | 1500 | 0.8537 | |
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| 0.7866 | 1.38 | 1600 | 0.8534 | |
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| 0.7224 | 1.46 | 1700 | 0.8480 | |
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| 0.7235 | 1.55 | 1800 | 0.8399 | |
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| 0.7936 | 1.64 | 1900 | 0.8385 | |
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| 0.7487 | 1.72 | 2000 | 0.8337 | |
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| 0.7842 | 1.81 | 2100 | 0.8284 | |
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| 0.7198 | 1.89 | 2200 | 0.8251 | |
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| 0.7507 | 1.98 | 2300 | 0.8188 | |
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| 0.622 | 2.07 | 2400 | 0.8353 | |
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| 0.6592 | 2.15 | 2500 | 0.8358 | |
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| 0.6043 | 2.24 | 2600 | 0.8330 | |
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| 0.7259 | 2.32 | 2700 | 0.8324 | |
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| 0.6388 | 2.41 | 2800 | 0.8290 | |
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| 0.7284 | 2.5 | 2900 | 0.8224 | |
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| 0.6166 | 2.58 | 3000 | 0.8202 | |
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| 0.6132 | 2.67 | 3100 | 0.8122 | |
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| 0.6323 | 2.75 | 3200 | 0.8094 | |
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| 0.6686 | 2.84 | 3300 | 0.8034 | |
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| 0.6457 | 2.93 | 3400 | 0.7991 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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