---
license: bigscience-bloom-rail-1.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: bigscience/bloom-560m
model-index:
- name: 4bit-emotion-detection
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 4bit-emotion-detection

This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co./bigscience/bloom-560m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1495
- Accuracy: 0.342
- F1: 0.3287

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 750
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 4.1982        | 1.0   | 250  | 4.4680          | 0.2805   | 0.2586 |
| 2.5719        | 2.0   | 500  | 2.4286          | 0.3145   | 0.3057 |
| 1.8911        | 3.0   | 750  | 2.1495          | 0.342    | 0.3287 |


### Framework versions

- PEFT 0.8.0
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.1