metadata
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
metrics:
- f1
- recall
- precision
model-index:
- name: sentiment-bloom-large-e6-v2
results: []
sentiment-bloom-large-e6-v2
This model is a fine-tuned version of LYTinn/bloom-finetuning-sentiment-model-3000-samples on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.4406
- F1: 0.6361
- Recall: 0.6361
- Precision: 0.6361
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: 4
- eval_batch_size: 4
- 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 | F1 | Recall | Precision |
|---|---|---|---|---|---|---|
| 0.9509 | 1.0 | 1500 | 1.7886 | 0.5822 | 0.5822 | 0.5822 |
| 0.7559 | 2.0 | 3000 | 3.0284 | 0.5930 | 0.5930 | 0.5930 |
| 0.5812 | 3.0 | 4500 | 3.5468 | 0.6388 | 0.6388 | 0.6388 |
| 0.2835 | 4.0 | 6000 | 4.7649 | 0.6442 | 0.6442 | 0.6442 |
| 0.1664 | 5.0 | 7500 | 5.4256 | 0.6361 | 0.6361 | 0.6361 |
| 0.0718 | 6.0 | 9000 | 5.4406 | 0.6361 | 0.6361 | 0.6361 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3