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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: office-character
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# office-character
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3380
- Accuracy: 0.3293
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3.3e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2896 | 0.09 | 200 | 2.3458 | 0.328 |
| 2.3881 | 0.18 | 400 | 2.3456 | 0.3207 |
| 2.3149 | 0.27 | 600 | 2.3552 | 0.3283 |
| 2.2579 | 0.36 | 800 | 2.3468 | 0.327 |
| 2.3016 | 0.45 | 1000 | 2.3512 | 0.327 |
| 2.3923 | 0.54 | 1200 | 2.3410 | 0.3313 |
| 2.3458 | 0.63 | 1400 | 2.3416 | 0.328 |
| 2.3522 | 0.72 | 1600 | 2.3303 | 0.3287 |
| 2.2485 | 0.81 | 1800 | 2.3291 | 0.3343 |
| 2.3083 | 0.9 | 2000 | 2.3289 | 0.3327 |
| 2.2594 | 0.99 | 2200 | 2.3336 | 0.3387 |
| 2.229 | 1.08 | 2400 | 2.3446 | 0.3213 |
| 2.3017 | 1.17 | 2600 | 2.3362 | 0.3327 |
| 2.2405 | 1.26 | 2800 | 2.3299 | 0.335 |
| 2.3291 | 1.35 | 3000 | 2.3291 | 0.33 |
| 2.2518 | 1.43 | 3200 | 2.3363 | 0.3297 |
| 2.268 | 1.52 | 3400 | 2.3623 | 0.3187 |
| 2.3198 | 1.61 | 3600 | 2.3480 | 0.3277 |
| 2.1873 | 1.7 | 3800 | 2.3355 | 0.3293 |
| 2.2634 | 1.79 | 4000 | 2.3291 | 0.326 |
| 2.1011 | 1.88 | 4200 | 2.3345 | 0.333 |
| 2.1965 | 1.97 | 4400 | 2.3383 | 0.3293 |
| 2.2368 | 2.06 | 4600 | 2.3320 | 0.329 |
| 2.2226 | 2.15 | 4800 | 2.3453 | 0.3263 |
| 2.2354 | 2.24 | 5000 | 2.3372 | 0.33 |
| 2.2829 | 2.33 | 5200 | 2.3547 | 0.3223 |
| 2.1544 | 2.42 | 5400 | 2.3336 | 0.3287 |
| 2.2777 | 2.51 | 5600 | 2.3425 | 0.3283 |
| 2.0763 | 2.6 | 5800 | 2.3339 | 0.3307 |
| 2.2738 | 2.69 | 6000 | 2.3389 | 0.3293 |
| 2.1013 | 2.78 | 6200 | 2.3411 | 0.327 |
| 2.1058 | 2.87 | 6400 | 2.3357 | 0.332 |
| 2.1621 | 2.96 | 6600 | 2.3380 | 0.3293 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
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