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  1. README.md +22 -4
  2. adapter_model.safetensors +1 -1
  3. runs/Apr22_01-30-18_e46554ad8bbb/events.out.tfevents.1713749420.e46554ad8bbb.34.0 +3 -0
  4. runs/Apr22_01-30-37_e46554ad8bbb/events.out.tfevents.1713749439.e46554ad8bbb.34.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Rocketknight1/falcon-rw-1b](https://huggingface.co/Rocketknight1/falcon-rw-1b) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9004
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  ## Model description
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@@ -43,15 +43,33 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.03
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- - num_epochs: 2
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.0238 | 0.99 | 77 | 0.9130 |
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- | 0.9371 | 1.98 | 154 | 0.9004 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Rocketknight1/falcon-rw-1b](https://huggingface.co/Rocketknight1/falcon-rw-1b) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4504
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 20
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.7984 | 0.99 | 77 | 0.7167 |
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+ | 0.7175 | 1.99 | 155 | 0.6955 |
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+ | 0.6092 | 2.99 | 233 | 0.6690 |
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+ | 0.5426 | 3.99 | 311 | 0.6549 |
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+ | 0.7676 | 5.0 | 389 | 0.6416 |
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+ | 0.6552 | 6.0 | 467 | 0.6216 |
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+ | 0.5989 | 7.0 | 545 | 0.6039 |
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+ | 0.4944 | 8.0 | 623 | 0.5810 |
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+ | 0.4591 | 8.99 | 700 | 0.5615 |
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+ | 0.5415 | 9.99 | 778 | 0.5429 |
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+ | 0.4794 | 10.99 | 856 | 0.5187 |
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+ | 0.4347 | 11.99 | 934 | 0.4982 |
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+ | 0.3487 | 13.0 | 1012 | 0.4845 |
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+ | 0.3229 | 14.0 | 1090 | 0.4724 |
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+ | 0.3946 | 15.0 | 1168 | 0.4624 |
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+ | 0.3689 | 16.0 | 1246 | 0.4574 |
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+ | 0.3191 | 16.99 | 1323 | 0.4529 |
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+ | 0.2793 | 17.99 | 1401 | 0.4509 |
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+ | 0.3675 | 18.99 | 1479 | 0.4504 |
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+ | 0.3215 | 19.78 | 1540 | 0.4504 |
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  ### Framework versions
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