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finetuning-sentiment-model-tweet-OLDsamples
DaisyQue/finetuning-sentiment-model-tweet-OLDsamples
finetuning-sentiment-model-tweet-OLDsamples is a text classification model from DaisyQue. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Nov 28, 2024
- Updated
- Nov 28, 2024
- SHA
- 25829738
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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. -->
finetuning-sentiment-model-tweet-OLDsamples
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3200
- Accuracy Percentage: 0.7738
- Accuracy Number: 65.0
- F1: 0.7878
- Precision: 0.7738
- Recall: 0.7738
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: 32
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Percentage | Accuracy Number | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.5465 | 1.0 | 11 | 0.5817 | 0.7857 | 66.0 | 0.7854 | 0.7857 | 0.7857 |
| 0.351 | 2.0 | 22 | 0.4817 | 0.7976 | 67.0 | 0.7930 | 0.7976 | 0.7976 |
| 0.1612 | 3.0 | 33 | 1.0279 | 0.75 | 63.0 | 0.7618 | 0.75 | 0.75 |
| 0.0734 | 4.0 | 44 | 1.0266 | 0.7857 | 66.0 | 0.7968 | 0.7857 | 0.7857 |
| 0.0303 | 5.0 | 55 | 0.8942 | 0.8095 | 68.0 | 0.8150 | 0.8095 | 0.8095 |
| 0.0083 | 6.0 | 66 | 1.1278 | 0.8095 | 68.0 | 0.8177 | 0.8095 | 0.8095 |
| 0.0028 | 7.0 | 77 | 1.2560 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 |
| 0.0012 | 8.0 | 88 | 1.2988 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 |
| 0.001 | 9.0 | 99 | 1.3170 | 0.7857 | 66.0 | 0.7997 | 0.7857 | 0.7857 |
| 0.001 | 10.0 | 110 | 1.3200 | 0.7738 | 65.0 | 0.7878 | 0.7738 | 0.7738 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Nov 28, 2024
- Updated
- Nov 28, 2024