File size: 2,654 Bytes
6902c3c |
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 75 |
---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch7
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. -->
# bertweet-base_3epoch7
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3665
- Accuracy: 0.7493
- F1: 0.4562
- Precision: 0.6033
- Recall: 0.3668
- Precision Sarcastic: 0.6033
- Recall Sarcastic: 0.3668
- F1 Sarcastic: 0.4562
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log | 1.0 | 174 | 0.9738 | 0.7378 | 0.2541 | 0.6889 | 0.1558 | 0.6889 | 0.1558 | 0.2541 |
| No log | 2.0 | 348 | 1.0669 | 0.7565 | 0.4459 | 0.6415 | 0.3417 | 0.6415 | 0.3417 | 0.4459 |
| 0.1251 | 3.0 | 522 | 1.2051 | 0.7493 | 0.4082 | 0.6316 | 0.3015 | 0.6316 | 0.3015 | 0.4082 |
| 0.1251 | 4.0 | 696 | 1.2494 | 0.7507 | 0.4401 | 0.6182 | 0.3417 | 0.6182 | 0.3417 | 0.4401 |
| 0.1251 | 5.0 | 870 | 1.3273 | 0.7507 | 0.4677 | 0.6032 | 0.3819 | 0.6032 | 0.3819 | 0.4677 |
| 0.0458 | 6.0 | 1044 | 1.3478 | 0.7493 | 0.4759 | 0.5940 | 0.3970 | 0.5940 | 0.3970 | 0.4759 |
| 0.0458 | 7.0 | 1218 | 1.3665 | 0.7493 | 0.4562 | 0.6033 | 0.3668 | 0.6033 | 0.3668 | 0.4562 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|