metadata
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: my_awesome_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: test
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.774
my_awesome_model
This model is a fine-tuned version of on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.6804
- Accuracy: 0.774
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6145 | 1.0 | 500 | 1.5603 | 0.3475 |
| 1.4622 | 2.0 | 1000 | 1.3149 | 0.4 |
| 1.2777 | 3.0 | 1500 | 1.2142 | 0.4365 |
| 1.1218 | 4.0 | 2000 | 1.0095 | 0.5915 |
| 0.8886 | 5.0 | 2500 | 0.8772 | 0.695 |
| 0.7649 | 6.0 | 3000 | 0.7803 | 0.7355 |
| 0.6818 | 7.0 | 3500 | 0.7220 | 0.7615 |
| 0.6268 | 8.0 | 4000 | 0.6870 | 0.773 |
| 0.5922 | 9.0 | 4500 | 0.6859 | 0.771 |
| 0.5658 | 10.0 | 5000 | 0.6804 | 0.774 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1