my-finetuned-emotion-distilbert
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.4044
Accuracy: 0.8360
F1: 0.8351
Precision: 0.8350
Recall: 0.8360
Classification Report: precision recall f1-score support
Class 0 0.84 0.87 0.86 87 Class 1 0.85 0.87 0.86 268 Class 2 0.80 0.75 0.77 151
accuracy 0.84 506 macro avg 0.83 0.83 0.83 506
weighted avg 0.84 0.84 0.84 506
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Classification Report |
---|---|---|---|---|---|---|---|---|
0.8199 | 1.0 | 72 | 0.5413 | 0.7964 | 0.7929 | 0.7946 | 0.7964 | precision recall f1-score support |
Class 0 0.83 0.78 0.80 87
Class 1 0.80 0.89 0.84 268
Class 2 0.76 0.64 0.70 151
accuracy 0.80 506
macro avg 0.80 0.77 0.78 506 weighted avg 0.79 0.80 0.79 506 | | 0.4627 | 2.0 | 144 | 0.4044 | 0.8360 | 0.8351 | 0.8350 | 0.8360 | precision recall f1-score support
Class 0 0.84 0.87 0.86 87
Class 1 0.85 0.87 0.86 268
Class 2 0.80 0.75 0.77 151
accuracy 0.84 506
macro avg 0.83 0.83 0.83 506 weighted avg 0.84 0.84 0.84 506 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for zijay/my-finetuned-emotion-distilbert
Base model
distilbert/distilbert-base-cased