metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT_tweet_tuned
results: []
BERT_tweet_tuned
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8264
- Accuracy: 0.6798
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: 5e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.56 | 100 | 0.6561 | 0.5455 |
| No log | 1.12 | 200 | 0.7148 | 0.6921 |
| No log | 1.68 | 300 | 0.6811 | 0.6712 |
| No log | 2.23 | 400 | 0.8286 | 0.6796 |
| 0.4781 | 2.79 | 500 | 0.8215 | 0.7005 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2