---
license: bigscience-bloom-rail-1.0
base_model: bigscience/bloom-560m
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: SciBLOOM-ft-TweetAreas-ES
  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. -->

# SciBLOOM-ft-TweetAreas-ES

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: 0.4180
- Roc Auc: 0.8398
- Hamming Loss: 0.0450
- F1 Score: 0.7555
- Accuracy: 0.4712
- Precision: 0.8527
- Recall: 0.7085

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| 0.2275        | 1.0   | 747  | 0.3007          | 0.7245  | 0.0797       | 0.5268   | 0.2838   | 0.8290    | 0.4840 |
| 0.1338        | 2.0   | 1494 | 0.2027          | 0.7985  | 0.0611       | 0.6307   | 0.3788   | 0.7336    | 0.6296 |
| 0.1244        | 3.0   | 2241 | 0.1917          | 0.7985  | 0.0564       | 0.6552   | 0.4070   | 0.7901    | 0.6354 |
| 0.0459        | 4.0   | 2988 | 0.2264          | 0.8247  | 0.0535       | 0.7187   | 0.4110   | 0.8199    | 0.6832 |
| 0.046         | 5.0   | 3735 | 0.2932          | 0.8103  | 0.0541       | 0.6862   | 0.4003   | 0.8026    | 0.6552 |
| 0.0305        | 6.0   | 4482 | 0.3364          | 0.8318  | 0.0509       | 0.7236   | 0.4378   | 0.8015    | 0.7008 |
| 0.0075        | 7.0   | 5229 | 0.4112          | 0.8326  | 0.0482       | 0.7348   | 0.4418   | 0.8164    | 0.6929 |
| 0.001         | 8.0   | 5976 | 0.3984          | 0.8358  | 0.0466       | 0.7507   | 0.4538   | 0.8501    | 0.7022 |
| 0.0           | 9.0   | 6723 | 0.4134          | 0.8448  | 0.0454       | 0.7591   | 0.4712   | 0.8447    | 0.7198 |
| 0.0           | 10.0  | 7470 | 0.4180          | 0.8398  | 0.0450       | 0.7555   | 0.4712   | 0.8527    | 0.7085 |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1