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---
base_model: keefezowie/my_awesome_model
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: 0.8295
---
<!-- 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. -->
# my_awesome_model
This model is a fine-tuned version of [keefezowie/my_awesome_model](https://huggingface.co/keefezowie/my_awesome_model) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7587
- Accuracy: 0.8295
## 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: 16
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3711 | 1.0 | 1000 | 1.1335 | 0.5795 |
| 0.7516 | 2.0 | 2000 | 0.6239 | 0.8065 |
| 0.5061 | 3.0 | 3000 | 0.5523 | 0.823 |
| 0.4381 | 4.0 | 4000 | 0.5857 | 0.8245 |
| 0.3637 | 5.0 | 5000 | 0.5661 | 0.839 |
| 0.3287 | 6.0 | 6000 | 0.5662 | 0.839 |
| 0.296 | 7.0 | 7000 | 0.6437 | 0.835 |
| 0.26 | 8.0 | 8000 | 0.6875 | 0.831 |
| 0.2344 | 9.0 | 9000 | 0.7239 | 0.8255 |
| 0.1989 | 10.0 | 10000 | 0.7587 | 0.8295 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
|