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sexism-detector-English-8812e-5001

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Files changed (8) hide show
  1. README.md +6 -6
  2. model.safetensors +1 -1
  3. runs/Nov25_21-47-06_9f15363db8c5/events.out.tfevents.1732571228.9f15363db8c5.1414.0 +3 -0
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  7. runs/Nov26_00-16-02_9f15363db8c5/events.out.tfevents.1732580163.9f15363db8c5.1414.4 +3 -0
  8. training_args.bin +1 -1
README.md CHANGED
@@ -8,18 +8,18 @@ metrics:
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  - accuracy
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  - f1
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  model-index:
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- - name: sexism-detector-English-8812e-5001
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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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- # sexism-detector-English-8812e-5001
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  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5550
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  - Accuracy: 0.7575
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  - F1: 0.6530
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@@ -41,8 +41,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -52,7 +52,7 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.5663 | 1.0 | 1750 | 0.5550 | 0.7575 | 0.6530 |
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  ### Framework versions
 
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  - accuracy
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  - f1
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  model-index:
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+ - name: sexism-detector-English-161612e-5001
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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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+ # sexism-detector-English-161612e-5001
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  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5543
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  - Accuracy: 0.7575
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  - F1: 0.6530
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.5667 | 1.0 | 875 | 0.5543 | 0.7575 | 0.6530 |
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  ### Framework versions
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