metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_lda_100_v1_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.7162327095199349
bert_base_lda_100_v1_mnli
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_100_v1 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6799
- Accuracy: 0.7162
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 |
|---|---|---|---|---|
| 0.9588 | 1.0 | 1534 | 0.8420 | 0.6249 |
| 0.7857 | 2.0 | 3068 | 0.7451 | 0.6808 |
| 0.6825 | 3.0 | 4602 | 0.7162 | 0.6976 |
| 0.5973 | 4.0 | 6136 | 0.7056 | 0.7113 |
| 0.5208 | 5.0 | 7670 | 0.7460 | 0.7144 |
| 0.4464 | 6.0 | 9204 | 0.7907 | 0.7078 |
| 0.3775 | 7.0 | 10738 | 0.8362 | 0.7172 |
| 0.316 | 8.0 | 12272 | 0.9463 | 0.7101 |
| 0.2617 | 9.0 | 13806 | 1.0094 | 0.7111 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3