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BLOOM-Meta4Types-ft-ES
alecmontero/BLOOM-Meta4Types-ft-ES
BLOOM-Meta4Types-ft-ES is a text classification model from alecmontero. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as bigscience-bloom-rail-1.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- bigscience-bloom-rail-1.0
- Model type
- bloom
- Access
- Public
- Created
- Aug 1, 2024
- Updated
- Aug 1, 2024
- SHA
- 58a160d6
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Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Text Classification
- Library
- transformers
- Type
- bloom
- License
- bigscience-bloom-rail-1.0
- Created
- Aug 1, 2024
- Updated
- Aug 1, 2024