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fine_tuned_per_domain_balanced_32B

Text Classification
Transformers
Safetensors
qwen2
Generated from Trainer
text-embeddings-inference
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Arihant Tripathi commited on
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qwen_new_mage_per_domain_balanced_32B

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Files changed (16) hide show
  1. README.md +15 -10
  2. evaluation_results.json +6 -6
  3. model-00001-of-00014.safetensors +1 -1
  4. model-00002-of-00014.safetensors +1 -1
  5. model-00003-of-00014.safetensors +1 -1
  6. model-00004-of-00014.safetensors +1 -1
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  8. model-00006-of-00014.safetensors +1 -1
  9. model-00007-of-00014.safetensors +1 -1
  10. model-00008-of-00014.safetensors +1 -1
  11. model-00009-of-00014.safetensors +1 -1
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README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Qwen/Qwen1.5-32B](https://huggingface.co/Qwen/Qwen1.5-32B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6290
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- - Accuracy: 0.9006
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  ## Model description
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@@ -50,14 +50,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.5509 | 0.0029 | 500 | 0.9119 | 0.7923 |
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- | 0.6879 | 0.0057 | 1000 | 0.8153 | 0.8371 |
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- | 0.9648 | 0.0086 | 1500 | 0.6872 | 0.8666 |
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- | 0.5438 | 0.0114 | 2000 | 0.6331 | 0.8809 |
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- | 1.0018 | 0.0143 | 2500 | 0.5661 | 0.8970 |
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- | 0.3358 | 0.0172 | 3000 | 0.6411 | 0.8953 |
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- | 0.3079 | 0.0200 | 3500 | 0.6068 | 0.8988 |
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- | 0.4419 | 0.0229 | 4000 | 0.6290 | 0.9006 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Qwen/Qwen1.5-32B](https://huggingface.co/Qwen/Qwen1.5-32B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5984
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+ - Accuracy: 0.9033
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.836 | 0.0029 | 500 | 0.8152 | 0.7914 |
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+ | 0.7087 | 0.0057 | 1000 | 0.8243 | 0.8371 |
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+ | 0.3183 | 0.0086 | 1500 | 0.6660 | 0.8630 |
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+ | 0.4053 | 0.0114 | 2000 | 0.6574 | 0.8756 |
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+ | 0.7241 | 0.0143 | 2500 | 0.7357 | 0.8729 |
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+ | 0.6671 | 0.0172 | 3000 | 0.7220 | 0.8774 |
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+ | 0.5065 | 0.0200 | 3500 | 0.6383 | 0.8962 |
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+ | 0.6733 | 0.0229 | 4000 | 0.6732 | 0.8881 |
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+ | 0.7698 | 0.0258 | 4500 | 0.6499 | 0.8845 |
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+ | 0.7928 | 0.0286 | 5000 | 0.5749 | 0.8979 |
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+ | 0.5598 | 0.0315 | 5500 | 0.5941 | 0.8962 |
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+ | 0.3074 | 0.0343 | 6000 | 0.5806 | 0.9015 |
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+ | 0.4272 | 0.0372 | 6500 | 0.5984 | 0.9033 |
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  ### Framework versions
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