metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_lda_5_v1_wnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glue
args: wnli
metrics:
- name: Accuracy
type: accuracy
value: 0.4507042253521127
distilbert_lda_5_v1_wnli
This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_5_v1 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.7299
- Accuracy: 0.4507
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7316 | 1.0 | 3 | 0.7449 | 0.3099 |
| 0.7137 | 2.0 | 6 | 0.7299 | 0.4507 |
| 0.7026 | 3.0 | 9 | 0.7607 | 0.2958 |
| 0.6937 | 4.0 | 12 | 0.7552 | 0.4930 |
| 0.7014 | 5.0 | 15 | 0.7826 | 0.2113 |
| 0.6909 | 6.0 | 18 | 0.8129 | 0.2394 |
| 0.6894 | 7.0 | 21 | 0.8085 | 0.2113 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3