File size: 2,266 Bytes
8b96faf
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b59e51e
 
 
 
8b96faf
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
619e606
 
 
8b96faf
619e606
8b96faf
 
 
619e606
ae71f03
8b96faf
 
 
 
b59e51e
 
 
 
 
 
 
 
8b96faf
 
 
 
ae71f03
8b96faf
 
ae71f03
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
---
library_name: transformers
license: cc-by-4.0
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mca-sentiment-analyzer-v2
  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. -->

# mca-sentiment-analyzer-v2

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1090
- Accuracy: 0.9668
- F1 Macro: 0.9673
- F1 Weighted: 0.9669

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 1.2893        | 0.1559 | 20   | 0.9350          | 0.6074   | 0.4810   | 0.4802      |
| 0.8368        | 0.3119 | 40   | 0.5051          | 0.8848   | 0.8833   | 0.8831      |
| 0.6255        | 0.4678 | 60   | 0.2471          | 0.9336   | 0.9341   | 0.9336      |
| 0.469         | 0.6238 | 80   | 0.1967          | 0.9297   | 0.9299   | 0.9295      |
| 0.3423        | 0.7797 | 100  | 0.1227          | 0.9551   | 0.9558   | 0.9553      |
| 0.3477        | 0.9357 | 120  | 0.1090          | 0.9668   | 0.9673   | 0.9669      |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0