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toxicity-scorer-smollm2-135m-it-freeze

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  1. README.md +11 -11
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: HuggingFaceTB/SmolLM2-135M
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -10,22 +10,22 @@ metrics:
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  - precision
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  - recall
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  model-index:
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- - name: toxicity-scorer-smollm2-135m-freeze
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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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- # toxicity-scorer-smollm2-135m-freeze
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- This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2939
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- - F1: 0.8645
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- - Accuracy: 0.8847
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- - Precision: 0.8636
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- - Recall: 0.8847
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  ## Model description
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@@ -61,8 +61,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
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- | No log | 0 | 0 | 1.5154 | 0.4459 | 0.3797 | 0.8101 | 0.3797 |
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- | 0.3001 | 1.5596 | 5000 | 0.2939 | 0.8645 | 0.8847 | 0.8636 | 0.8847 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: HuggingFaceTB/SmolLM2-135M-Instruct
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  - precision
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  - recall
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  model-index:
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+ - name: toxicity-scorer-smollm2-135m-it-freeze
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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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+ # toxicity-scorer-smollm2-135m-it-freeze
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+ This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3147
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+ - F1: 0.8264
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+ - Accuracy: 0.8745
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+ - Precision: 0.8384
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+ - Recall: 0.8745
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
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+ | No log | 0 | 0 | 0.9227 | 0.6386 | 0.5685 | 0.7480 | 0.5685 |
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+ | 0.3196 | 1.5596 | 5000 | 0.3147 | 0.8264 | 0.8745 | 0.8384 | 0.8745 |
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  ### Framework versions
model.safetensors CHANGED
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