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terceraprueba
miguelpezo/terceraprueba
terceraprueba is a text classification model from miguelpezo. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024
- SHA
- dda06179
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Base models
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. -->
terceraprueba
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0397
- Accuracy: 0.54
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6369 | 0.16 | 20 | 1.6191 | 0.25 |
| 1.6334 | 0.32 | 40 | 1.5859 | 0.24 |
| 1.6161 | 0.48 | 60 | 1.6090 | 0.26 |
| 1.6157 | 0.64 | 80 | 1.6140 | 0.155 |
| 1.62 | 0.8 | 100 | 1.6157 | 0.22 |
| 1.6311 | 0.96 | 120 | 1.6024 | 0.24 |
| 1.629 | 1.12 | 140 | 1.6102 | 0.165 |
| 1.6211 | 1.28 | 160 | 1.6152 | 0.22 |
| 1.6273 | 1.44 | 180 | 1.6083 | 0.22 |
| 1.6293 | 1.6 | 200 | 1.6101 | 0.22 |
| 1.6283 | 1.76 | 220 | 1.6101 | 0.25 |
| 1.6239 | 1.92 | 240 | 1.6072 | 0.245 |
| 1.6095 | 2.08 | 260 | 1.5872 | 0.27 |
| 1.6145 | 2.24 | 280 | 1.6071 | 0.22 |
| 1.6052 | 2.4 | 300 | 1.5858 | 0.235 |
| 1.5458 | 2.56 | 320 | 1.3771 | 0.4 |
| 1.4475 | 2.7200 | 340 | 1.4233 | 0.375 |
| 1.4089 | 2.88 | 360 | 1.4001 | 0.4 |
| 1.5145 | 3.04 | 380 | 1.4117 | 0.385 |
| 1.3812 | 3.2 | 400 | 1.4008 | 0.375 |
| 1.427 | 3.36 | 420 | 1.3099 | 0.42 |
| 1.378 | 3.52 | 440 | 1.2759 | 0.455 |
| 1.386 | 3.68 | 460 | 1.3181 | 0.4 |
| 1.2394 | 3.84 | 480 | 1.1192 | 0.47 |
| 1.1776 | 4.0 | 500 | 1.0973 | 0.47 |
| 1.0816 | 4.16 | 520 | 1.1384 | 0.42 |
| 1.1577 | 4.32 | 540 | 1.0555 | 0.51 |
| 1.0716 | 4.48 | 560 | 1.0644 | 0.51 |
| 1.0234 | 4.64 | 580 | 1.0456 | 0.535 |
| 0.9915 | 4.8 | 600 | 1.0481 | 0.5 |
| 0.9612 | 4.96 | 620 | 1.0397 | 0.54 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024