metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16class_all9k_promptcorr_tweet_300other_23nov23_v1
results: []
16class_all9k_promptcorr_tweet_300other_23nov23_v1
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0267
- Accuracy: 0.9947
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: 1e-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: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5225 | 1.0 | 721 | 0.6075 | 0.8344 |
| 0.7164 | 2.0 | 1442 | 0.3430 | 0.9051 |
| 0.3828 | 3.0 | 2163 | 0.2532 | 0.9271 |
| 0.318 | 4.0 | 2884 | 0.1631 | 0.9572 |
| 0.2131 | 5.0 | 3605 | 0.1231 | 0.9676 |
| 0.1728 | 6.0 | 4326 | 0.0822 | 0.9807 |
| 0.1344 | 7.0 | 5047 | 0.0657 | 0.9849 |
| 0.0902 | 8.0 | 5768 | 0.0471 | 0.9887 |
| 0.0842 | 9.0 | 6489 | 0.0383 | 0.9912 |
| 0.0609 | 10.0 | 7210 | 0.0281 | 0.9941 |
| 0.0512 | 11.0 | 7931 | 0.0267 | 0.9947 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0