Downloads · 30 days
3
12% of all-time downloads
fine_tune_sentiment_analysis_fin
abbysAI/fine_tune_sentiment_analysis_fin
fine_tune_sentiment_analysis_fin is a text classification model from abbysAI. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
25
Public
Parameters
67M
1.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jan 12, 2025
- Updated
- Jan 13, 2025
- SHA
- 0ac94888
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
fine_tune_sentiment_analysis_fin
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4803
- Mse: 0.3574
- Mae: 0.5231
- R2: -0.0000
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: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 19 | 0.3604 | 0.3574 | 0.5231 | -0.0000 |
| No log | 2.0 | 38 | 0.3654 | 0.3574 | 0.5231 | -0.0000 |
| No log | 3.0 | 57 | 0.3713 | 0.3574 | 0.5231 | -0.0000 |
| No log | 4.0 | 76 | 0.3799 | 0.3574 | 0.5231 | -0.0000 |
| No log | 5.0 | 95 | 0.3796 | 0.3574 | 0.5231 | -0.0000 |
| No log | 6.0 | 114 | 0.3925 | 0.3574 | 0.5231 | -0.0000 |
| No log | 7.0 | 133 | 0.3793 | 0.3574 | 0.5231 | -0.0000 |
| No log | 8.0 | 152 | 0.3993 | 0.3574 | 0.5231 | -0.0000 |
| No log | 9.0 | 171 | 0.3957 | 0.3574 | 0.5231 | -0.0000 |
| No log | 10.0 | 190 | 0.4051 | 0.3574 | 0.5231 | -0.0000 |
| No log | 11.0 | 209 | 0.4216 | 0.3574 | 0.5231 | -0.0000 |
| No log | 12.0 | 228 | 0.4195 | 0.3574 | 0.5231 | -0.0000 |
| No log | 13.0 | 247 | 0.4499 | 0.3574 | 0.5231 | -0.0000 |
| No log | 14.0 | 266 | 0.4140 | 0.3574 | 0.5231 | -0.0000 |
| No log | 15.0 | 285 | 0.4346 | 0.3574 | 0.5231 | -0.0000 |
| No log | 16.0 | 304 | 0.4319 | 0.3574 | 0.5231 | -0.0000 |
| No log | 17.0 | 323 | 0.4504 | 0.3574 | 0.5231 | -0.0000 |
| No log | 18.0 | 342 | 0.4391 | 0.3574 | 0.5231 | -0.0000 |
| No log | 19.0 | 361 | 0.4549 | 0.3574 | 0.5231 | -0.0000 |
| No log | 20.0 | 380 | 0.4656 | 0.3574 | 0.5231 | -0.0000 |
| No log | 21.0 | 399 | 0.4536 | 0.3574 | 0.5231 | -0.0000 |
| No log | 22.0 | 418 | 0.4621 | 0.3574 | 0.5231 | -0.0000 |
| No log | 23.0 | 437 | 0.4709 | 0.3574 | 0.5231 | -0.0000 |
| No log | 24.0 | 456 | 0.4806 | 0.3574 | 0.5231 | -0.0000 |
| No log | 25.0 | 475 | 0.4725 | 0.3574 | 0.5231 | -0.0000 |
| No log | 26.0 | 494 | 0.4713 | 0.3574 | 0.5231 | -0.0000 |
| 0.2837 | 27.0 | 513 | 0.4697 | 0.3574 | 0.5231 | -0.0000 |
| 0.2837 | 28.0 | 532 | 0.4768 | 0.3574 | 0.5231 | -0.0000 |
| 0.2837 | 29.0 | 551 | 0.4795 | 0.3574 | 0.5231 | -0.0000 |
| 0.2837 | 30.0 | 570 | 0.4803 | 0.3574 | 0.5231 | -0.0000 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 12, 2025
- Updated
- Jan 13, 2025