metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-finetuned-nlp-letters-s1_s2-all-class-weighted
results: []
distilbert-base-uncased-finetuned-nlp-letters-s1_s2-all-class-weighted
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9111
- F1: 0.7954
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 221 | 0.4314 | 0.5764 |
| No log | 2.0 | 442 | 0.3605 | 0.7050 |
| 0.4222 | 3.0 | 663 | 0.3836 | 0.6435 |
| 0.4222 | 4.0 | 884 | 0.8083 | 0.7664 |
| 0.2007 | 5.0 | 1105 | 1.2276 | 0.7810 |
| 0.2007 | 6.0 | 1326 | 1.9111 | 0.7954 |
| 0.0691 | 7.0 | 1547 | 1.7697 | 0.7767 |
| 0.0691 | 8.0 | 1768 | 1.7481 | 0.7758 |
| 0.0691 | 9.0 | 1989 | 1.7456 | 0.7755 |
| 0.0179 | 10.0 | 2210 | 1.9461 | 0.7848 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1