File size: 1,886 Bytes
e9dbdb3 |
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-multilingual
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-finetuned-language-detection
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. -->
# xlm-roberta-base-finetuned-language-detection
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5624
- Accuracy: 0.8195
- F1: 0.8195
## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5881 | 1.0 | 941 | 0.5179 | 0.7917 | 0.7915 |
| 0.4524 | 2.0 | 1882 | 0.5121 | 0.8097 | 0.8103 |
| 0.3749 | 3.0 | 2823 | 0.5268 | 0.8142 | 0.8142 |
| 0.3159 | 4.0 | 3764 | 0.5388 | 0.8176 | 0.8176 |
| 0.2721 | 5.0 | 4705 | 0.5624 | 0.8195 | 0.8195 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|