transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_5_v1_book base_model:finetune:gokulsrinivasagan/distilbert_lda_5_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_5_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_5_v1_book_rte
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - type: accuracy
      value: 0.5812274368231047
      name: Accuracy
---

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# distilbert_lda_5_v1_book_rte

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1_book) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6748
- Accuracy: 0.5812

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7084        | 1.0   | 10   | 0.7007          | 0.4729   |
| 0.6894        | 2.0   | 20   | 0.6887          | 0.5271   |
| 0.6725        | 3.0   | 30   | 0.6748          | 0.5812   |
| 0.6047        | 4.0   | 40   | 0.7342          | 0.5812   |
| 0.5014        | 5.0   | 50   | 0.8410          | 0.5884   |
| 0.3728        | 6.0   | 60   | 0.8730          | 0.6101   |
| 0.2546        | 7.0   | 70   | 1.0910          | 0.5957   |
| 0.1889        | 8.0   | 80   | 1.1483          | 0.5848   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1
