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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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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model-index: |
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- name: office-character |
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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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# office-character |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3380 |
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- Accuracy: 0.3293 |
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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: 3.3e-06 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.2896 | 0.09 | 200 | 2.3458 | 0.328 | |
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| 2.3881 | 0.18 | 400 | 2.3456 | 0.3207 | |
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| 2.3149 | 0.27 | 600 | 2.3552 | 0.3283 | |
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| 2.2579 | 0.36 | 800 | 2.3468 | 0.327 | |
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| 2.3016 | 0.45 | 1000 | 2.3512 | 0.327 | |
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| 2.3923 | 0.54 | 1200 | 2.3410 | 0.3313 | |
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| 2.3458 | 0.63 | 1400 | 2.3416 | 0.328 | |
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| 2.3522 | 0.72 | 1600 | 2.3303 | 0.3287 | |
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| 2.2485 | 0.81 | 1800 | 2.3291 | 0.3343 | |
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| 2.3083 | 0.9 | 2000 | 2.3289 | 0.3327 | |
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| 2.2594 | 0.99 | 2200 | 2.3336 | 0.3387 | |
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| 2.229 | 1.08 | 2400 | 2.3446 | 0.3213 | |
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| 2.3017 | 1.17 | 2600 | 2.3362 | 0.3327 | |
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| 2.2405 | 1.26 | 2800 | 2.3299 | 0.335 | |
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| 2.3291 | 1.35 | 3000 | 2.3291 | 0.33 | |
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| 2.2518 | 1.43 | 3200 | 2.3363 | 0.3297 | |
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| 2.268 | 1.52 | 3400 | 2.3623 | 0.3187 | |
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| 2.3198 | 1.61 | 3600 | 2.3480 | 0.3277 | |
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| 2.1873 | 1.7 | 3800 | 2.3355 | 0.3293 | |
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| 2.2634 | 1.79 | 4000 | 2.3291 | 0.326 | |
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| 2.1011 | 1.88 | 4200 | 2.3345 | 0.333 | |
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| 2.1965 | 1.97 | 4400 | 2.3383 | 0.3293 | |
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| 2.2368 | 2.06 | 4600 | 2.3320 | 0.329 | |
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| 2.2226 | 2.15 | 4800 | 2.3453 | 0.3263 | |
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| 2.2354 | 2.24 | 5000 | 2.3372 | 0.33 | |
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| 2.2829 | 2.33 | 5200 | 2.3547 | 0.3223 | |
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| 2.1544 | 2.42 | 5400 | 2.3336 | 0.3287 | |
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| 2.2777 | 2.51 | 5600 | 2.3425 | 0.3283 | |
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| 2.0763 | 2.6 | 5800 | 2.3339 | 0.3307 | |
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| 2.2738 | 2.69 | 6000 | 2.3389 | 0.3293 | |
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| 2.1013 | 2.78 | 6200 | 2.3411 | 0.327 | |
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| 2.1058 | 2.87 | 6400 | 2.3357 | 0.332 | |
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| 2.1621 | 2.96 | 6600 | 2.3380 | 0.3293 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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