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--- |
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library_name: transformers |
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base_model: KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: dfm_indirect_speech |
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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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# dfm_indirect_speech |
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This model is a fine-tuned version of [KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align](https://huggingface.co/KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.9158 |
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- Precision: 0.9150 |
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- Recall: 0.9158 |
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- F1: 0.9099 |
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- Loss: 0.6465 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.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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- 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 | Accuracy | Precision | Recall | F1 | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:| |
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| No log | 1.0 | 13 | 0.8602 | 0.8484 | 0.8602 | 0.8492 | 0.4979 | |
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| No log | 2.0 | 26 | 0.8809 | 0.8636 | 0.8809 | 0.8718 | 0.4677 | |
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| No log | 3.0 | 39 | 0.9062 | 0.8906 | 0.9062 | 0.8973 | 0.3820 | |
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| No log | 4.0 | 52 | 0.9290 | 0.9110 | 0.9290 | 0.9194 | 0.4183 | |
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| No log | 5.0 | 65 | 0.9018 | 0.8924 | 0.9018 | 0.8958 | 0.3585 | |
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| No log | 6.0 | 78 | 0.8939 | 0.8984 | 0.8939 | 0.8855 | 0.5402 | |
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| No log | 7.0 | 91 | 0.9171 | 0.9105 | 0.9171 | 0.9131 | 0.4350 | |
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| No log | 8.0 | 104 | 0.9255 | 0.9198 | 0.9255 | 0.9196 | 0.4858 | |
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| No log | 9.0 | 117 | 0.9242 | 0.9259 | 0.9242 | 0.9161 | 0.5378 | |
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| No log | 10.0 | 130 | 0.9177 | 0.9153 | 0.9177 | 0.9114 | 0.5865 | |
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| No log | 11.0 | 143 | 0.9181 | 0.9169 | 0.9181 | 0.9120 | 0.6122 | |
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| No log | 12.0 | 156 | 0.9163 | 0.9154 | 0.9163 | 0.9102 | 0.6229 | |
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| No log | 13.0 | 169 | 0.9165 | 0.9146 | 0.9165 | 0.9106 | 0.6222 | |
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| No log | 14.0 | 182 | 0.9154 | 0.9127 | 0.9154 | 0.9096 | 0.6227 | |
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| No log | 15.0 | 195 | 0.9146 | 0.9141 | 0.9146 | 0.9088 | 0.6326 | |
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| No log | 16.0 | 208 | 0.9154 | 0.9146 | 0.9154 | 0.9095 | 0.6406 | |
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| No log | 17.0 | 221 | 0.9154 | 0.9146 | 0.9154 | 0.9095 | 0.6462 | |
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| No log | 18.0 | 234 | 0.9158 | 0.9150 | 0.9158 | 0.9099 | 0.6458 | |
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| No log | 18.48 | 240 | 0.9158 | 0.9150 | 0.9158 | 0.9099 | 0.6465 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Tokenizers 0.21.0 |
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