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---
base_model: gokuls/bert_12_layer_model_v4_complete_training_48
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v4_48_emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: split
split: validation
args: split
metrics:
- name: Accuracy
type: accuracy
value: 0.4455
---
<!-- 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. -->
# bert_12_layer_model_v4_48_emotion
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v4_complete_training_48](https://huggingface.co/gokuls/bert_12_layer_model_v4_complete_training_48) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5438
- Accuracy: 0.4455
## 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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.605 | 1.0 | 250 | 1.5438 | 0.4455 |
| 1.5564 | 2.0 | 500 | 1.6343 | 0.318 |
| 1.5893 | 3.0 | 750 | 1.5894 | 0.31 |
| 1.5839 | 4.0 | 1000 | 1.5841 | 0.3505 |
| 1.5879 | 5.0 | 1250 | 1.6087 | 0.275 |
| 1.5892 | 6.0 | 1500 | 1.5838 | 0.352 |
| 1.5819 | 7.0 | 1750 | 1.5755 | 0.3465 |
| 1.5766 | 8.0 | 2000 | 1.5800 | 0.347 |
| 1.5745 | 9.0 | 2250 | 1.5768 | 0.3505 |
| 1.5717 | 10.0 | 2500 | 1.5774 | 0.3455 |
### Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
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