File size: 2,011 Bytes
de85397 fa76974 de85397 fa76974 de85397 fa76974 de85397 fa76974 de85397 fa76974 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
tags:
- generated_from_trainer
model-index:
- name: Analisis-sentimientos-XLM-Roberta-TASS-C
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. -->
# Analisis-sentimientos-XLM-Roberta-TASS-C
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9503
- F1-score: 0.6139
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9136 | 1.0 | 241 | 0.8427 | 0.6223 |
| 0.6957 | 2.0 | 482 | 0.9260 | 0.6046 |
| 0.4825 | 3.0 | 723 | 1.1533 | 0.6004 |
| 0.299 | 4.0 | 964 | 1.2836 | 0.5952 |
| 0.2142 | 5.0 | 1205 | 1.5988 | 0.6160 |
| 0.1312 | 6.0 | 1446 | 2.5332 | 0.5879 |
| 0.0899 | 7.0 | 1687 | 2.4297 | 0.6233 |
| 0.0414 | 8.0 | 1928 | 2.7368 | 0.6129 |
| 0.023 | 9.0 | 2169 | 2.9262 | 0.6160 |
| 0.0203 | 10.0 | 2410 | 2.9503 | 0.6139 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
|