File size: 2,244 Bytes
f7169f7 24382d6 f7169f7 24382d6 f7169f7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-classifier
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. -->
# distilbert-base-uncased-classifier
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2505
- Accuracy: 0.8919
- F1: 0.7899
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log | 0 | 0 | 0.6737 | 0.7493 | 0.0440 |
| No log | 0.2020 | 79 | 0.3465 | 0.8602 | 0.6820 |
| No log | 0.4041 | 158 | 0.3404 | 0.8458 | 0.7371 |
| No log | 0.6061 | 237 | 0.2951 | 0.8761 | 0.7650 |
| No log | 0.8082 | 316 | 0.2763 | 0.8862 | 0.7893 |
| No log | 1.0102 | 395 | 0.2732 | 0.8818 | 0.7747 |
| No log | 1.2123 | 474 | 0.2707 | 0.8905 | 0.7865 |
| 0.3426 | 1.4143 | 553 | 0.2516 | 0.8963 | 0.7989 |
| 0.3426 | 1.6164 | 632 | 0.2434 | 0.8963 | 0.7943 |
| 0.3426 | 1.8184 | 711 | 0.2505 | 0.8919 | 0.7899 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
|