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./lora_adapter_bart_on_eu
Browse files- README.md +40 -12
- adapter_model.safetensors +1 -1
README.md
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tags:
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- generated_from_trainer
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base_model: facebook/bart-large-mnli
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model-index:
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- name: finetuned_bart
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results: []
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This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- eval_runtime: 45.0597
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- eval_samples_per_second: 163.095
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- eval_steps_per_second: 2.552
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- epoch: 1.9403
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- step: 1040
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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### Framework versions
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tags:
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- generated_from_trainer
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base_model: facebook/bart-large-mnli
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metrics:
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- f1
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- precision
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- recall
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- accuracy
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model-index:
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- name: finetuned_bart
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results: []
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This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0620
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- F1: 0.9236
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- Precision: 0.9000
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- Recall: 0.9485
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- Accuracy: 0.9216
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## Model description
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### Training hyperparameters
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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: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 20
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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| 0.0856 | 0.0933 | 50 | 0.0695 | 0.9122 | 0.9010 | 0.9238 | 0.9111 |
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| 0.0593 | 0.1866 | 100 | 0.0685 | 0.9152 | 0.8970 | 0.9341 | 0.9135 |
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| 0.0572 | 0.2799 | 150 | 0.0681 | 0.9149 | 0.8997 | 0.9306 | 0.9135 |
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| 0.0549 | 0.3731 | 200 | 0.0679 | 0.9150 | 0.9054 | 0.9249 | 0.9141 |
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| 0.0529 | 0.4664 | 250 | 0.0678 | 0.9174 | 0.9043 | 0.9308 | 0.9162 |
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| 0.0776 | 0.5597 | 300 | 0.0673 | 0.9158 | 0.9079 | 0.9238 | 0.9151 |
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| 0.0799 | 0.6530 | 350 | 0.0647 | 0.9201 | 0.8964 | 0.9450 | 0.9179 |
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| 0.0806 | 0.7463 | 400 | 0.0647 | 0.9196 | 0.8968 | 0.9436 | 0.9175 |
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| 0.0781 | 0.8396 | 450 | 0.0635 | 0.9193 | 0.8982 | 0.9415 | 0.9174 |
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| 0.0771 | 0.9328 | 500 | 0.0633 | 0.9189 | 0.9019 | 0.9366 | 0.9174 |
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| 0.0787 | 1.0261 | 550 | 0.0629 | 0.9202 | 0.8994 | 0.9420 | 0.9184 |
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| 0.0737 | 1.1194 | 600 | 0.0627 | 0.9210 | 0.8989 | 0.9442 | 0.9190 |
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| 0.0722 | 1.2127 | 650 | 0.0634 | 0.9212 | 0.8981 | 0.9455 | 0.9192 |
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| 0.0684 | 1.3060 | 700 | 0.0630 | 0.9217 | 0.9065 | 0.9374 | 0.9204 |
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| 0.0655 | 1.3993 | 750 | 0.0629 | 0.9228 | 0.8974 | 0.9496 | 0.9205 |
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| 0.0739 | 1.4925 | 800 | 0.0625 | 0.9229 | 0.8993 | 0.9477 | 0.9208 |
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| 0.0666 | 1.5858 | 850 | 0.0625 | 0.9233 | 0.8962 | 0.9521 | 0.9209 |
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| 0.0703 | 1.6791 | 900 | 0.0621 | 0.9238 | 0.9001 | 0.9488 | 0.9218 |
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| 0.0738 | 1.7724 | 950 | 0.0617 | 0.9227 | 0.9007 | 0.9458 | 0.9208 |
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| 0.068 | 1.8657 | 1000 | 0.0620 | 0.9233 | 0.9002 | 0.9477 | 0.9213 |
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| 0.069 | 1.9590 | 1050 | 0.0620 | 0.9236 | 0.9000 | 0.9485 | 0.9216 |
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### Framework versions
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adapter_model.safetensors
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