metadata
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_lda_100_v1_book_rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.5270758122743683
distilbert_lda_100_v1_book_rte
This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1_book on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6902
- Accuracy: 0.5271
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 OptimizerNames.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 |
---|---|---|---|---|
0.7006 | 1.0 | 10 | 0.6935 | 0.4765 |
0.6908 | 2.0 | 20 | 0.6908 | 0.5199 |
0.6809 | 3.0 | 30 | 0.6902 | 0.5271 |
0.6542 | 4.0 | 40 | 0.6959 | 0.5343 |
0.5813 | 5.0 | 50 | 0.7287 | 0.5560 |
0.4761 | 6.0 | 60 | 0.7502 | 0.5632 |
0.3513 | 7.0 | 70 | 0.8904 | 0.5776 |
0.2219 | 8.0 | 80 | 1.1421 | 0.5415 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1