metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hasoc19-bert-base-multilingual-uncased-sentiment-new
results: []
hasoc19-bert-base-multilingual-uncased-sentiment-new
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4879
- Accuracy: 0.8433
- Precision: 0.8441
- Recall: 0.8433
- F1: 0.8436
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.4931 | 1.0 | 537 | 0.4011 | 0.8192 | 0.8212 | 0.8192 | 0.8198 |
0.3643 | 2.0 | 1074 | 0.4020 | 0.8291 | 0.8298 | 0.8291 | 0.8294 |
0.2816 | 3.0 | 1611 | 0.3837 | 0.8339 | 0.8378 | 0.8339 | 0.8347 |
0.2378 | 4.0 | 2148 | 0.4235 | 0.8381 | 0.8378 | 0.8381 | 0.8379 |
0.1904 | 5.0 | 2685 | 0.4753 | 0.8349 | 0.8350 | 0.8349 | 0.8349 |
0.1597 | 6.0 | 3222 | 0.4879 | 0.8433 | 0.8441 | 0.8433 | 0.8436 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1