File size: 2,297 Bytes
e871edb |
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 68 69 70 71 72 73 74 |
---
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-xlm-attempt2
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. -->
# Improved-xlm-attempt2
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: 0.3637
- Accuracy: 0.87
## 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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.07 | 50 | 0.4087 | 0.86 |
| No log | 0.14 | 100 | 0.3930 | 0.86 |
| No log | 0.21 | 150 | 0.4688 | 0.79 |
| No log | 0.27 | 200 | 0.3834 | 0.82 |
| No log | 0.34 | 250 | 0.4249 | 0.83 |
| No log | 0.41 | 300 | 0.5777 | 0.8 |
| No log | 0.48 | 350 | 0.4752 | 0.82 |
| No log | 0.55 | 400 | 0.3080 | 0.89 |
| No log | 0.62 | 450 | 0.4125 | 0.83 |
| 0.3475 | 0.68 | 500 | 0.3273 | 0.9 |
| 0.3475 | 0.75 | 550 | 0.6456 | 0.77 |
| 0.3475 | 0.82 | 600 | 0.6110 | 0.77 |
| 0.3475 | 0.89 | 650 | 0.3898 | 0.85 |
| 0.3475 | 0.96 | 700 | 0.4062 | 0.87 |
| 0.3475 | 1.03 | 750 | 0.3637 | 0.87 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
|