---
license: bigscience-bloom-rail-1.0
base_model: bigscience/bloomz-560m
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: BLOOM-Meta4Types-ft-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. -->

# BLOOM-Meta4Types-ft-ES

This model is a fine-tuned version of [bigscience/bloomz-560m](https://huggingface.co/bigscience/bloomz-560m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6658
- Roc Auc: 0.6521
- Hamming Loss: 0.2255
- F1 Score: 0.5792
- Accuracy: 0.5098
- Precision: 0.5611
- Recall: 0.6085

## 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: 5e-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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 204  | 1.4085          | 0.5227  | 0.3775       | 0.0874   | 0.0490   | 0.9333    | 0.0500 |
| No log        | 2.0   | 408  | 1.3092          | 0.5569  | 0.4036       | 0.3425   | 0.2353   | 0.7464    | 0.4360 |
| 1.9965        | 3.0   | 612  | 1.2200          | 0.5497  | 0.2304       | 0.4634   | 0.4510   | 0.7327    | 0.5574 |
| 1.9965        | 4.0   | 816  | 1.4996          | 0.5843  | 0.3235       | 0.3965   | 0.3922   | 0.4177    | 0.4519 |
| 0.6193        | 5.0   | 1020 | 1.0759          | 0.5823  | 0.2271       | 0.4488   | 0.5098   | 0.6180    | 0.4070 |
| 0.6193        | 6.0   | 1224 | 1.8243          | 0.5808  | 0.2614       | 0.4892   | 0.3775   | 0.5688    | 0.5824 |
| 0.6193        | 7.0   | 1428 | 1.6658          | 0.6521  | 0.2255       | 0.5792   | 0.5098   | 0.5611    | 0.6085 |
| 0.202         | 8.0   | 1632 | 2.0491          | 0.5856  | 0.2075       | 0.4864   | 0.5441   | 0.5844    | 0.4447 |
| 0.202         | 9.0   | 1836 | 2.2174          | 0.6241  | 0.1944       | 0.5733   | 0.5588   | 0.6183    | 0.5504 |
| 0.0338        | 10.0  | 2040 | 2.1754          | 0.6265  | 0.1993       | 0.5693   | 0.5539   | 0.6197    | 0.5399 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1