metadata
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: add_BERT_48_sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
config: sst2
split: validation
args: sst2
metrics:
- name: Accuracy
type: accuracy
value: 0.8027522935779816
add_BERT_48_sst2
This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new_48 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4410
- Accuracy: 0.8028
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4532 | 1.0 | 527 | 0.4410 | 0.8028 |
| 0.2621 | 2.0 | 1054 | 0.4674 | 0.8073 |
| 0.2037 | 3.0 | 1581 | 0.4985 | 0.8005 |
| 0.1699 | 4.0 | 2108 | 0.5998 | 0.7959 |
| 0.1441 | 5.0 | 2635 | 0.6110 | 0.7821 |
| 0.1238 | 6.0 | 3162 | 0.6674 | 0.8165 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3