---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- trl
- reward-trainer
- generated_from_trainer
datasets:
- hdfs_rlhf_log_summary_dataset
metrics:
- accuracy
model-index:
- name: log_sage_reward_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: hdfs_rlhf_log_summary_dataset
      type: hdfs_rlhf_log_summary_dataset
      config: default
      split: None
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# log_sage_reward_model

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the hdfs_rlhf_log_summary_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1669
- Accuracy: 1.0

## 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: 1.41e-05
- train_batch_size: 6
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6950          | 0.5      |
| No log        | 2.0   | 2    | 0.6896          | 1.0      |
| No log        | 3.0   | 3    | 0.6843          | 1.0      |
| No log        | 4.0   | 4    | 0.6789          | 1.0      |
| No log        | 5.0   | 5    | 0.6735          | 1.0      |
| No log        | 6.0   | 6    | 0.6671          | 1.0      |
| No log        | 7.0   | 7    | 0.6597          | 1.0      |
| No log        | 8.0   | 8    | 0.6510          | 1.0      |
| No log        | 9.0   | 9    | 0.6403          | 1.0      |
| 0.0839        | 10.0  | 10   | 0.6275          | 1.0      |
| 0.0839        | 11.0  | 11   | 0.6130          | 1.0      |
| 0.0839        | 12.0  | 12   | 0.5955          | 1.0      |
| 0.0839        | 13.0  | 13   | 0.5747          | 1.0      |
| 0.0839        | 14.0  | 14   | 0.5508          | 1.0      |
| 0.0839        | 15.0  | 15   | 0.5250          | 1.0      |
| 0.0839        | 16.0  | 16   | 0.4984          | 1.0      |
| 0.0839        | 17.0  | 17   | 0.4698          | 1.0      |
| 0.0839        | 18.0  | 18   | 0.4413          | 1.0      |
| 0.0839        | 19.0  | 19   | 0.4121          | 1.0      |
| 0.0658        | 20.0  | 20   | 0.3850          | 1.0      |
| 0.0658        | 21.0  | 21   | 0.3604          | 1.0      |
| 0.0658        | 22.0  | 22   | 0.3384          | 1.0      |
| 0.0658        | 23.0  | 23   | 0.3186          | 1.0      |
| 0.0658        | 24.0  | 24   | 0.2995          | 1.0      |
| 0.0658        | 25.0  | 25   | 0.2823          | 1.0      |
| 0.0658        | 26.0  | 26   | 0.2664          | 1.0      |
| 0.0658        | 27.0  | 27   | 0.2516          | 1.0      |
| 0.0658        | 28.0  | 28   | 0.2384          | 1.0      |
| 0.0658        | 29.0  | 29   | 0.2260          | 1.0      |
| 0.0346        | 30.0  | 30   | 0.2149          | 1.0      |
| 0.0346        | 31.0  | 31   | 0.2054          | 1.0      |
| 0.0346        | 32.0  | 32   | 0.1971          | 1.0      |
| 0.0346        | 33.0  | 33   | 0.1898          | 1.0      |
| 0.0346        | 34.0  | 34   | 0.1838          | 1.0      |
| 0.0346        | 35.0  | 35   | 0.1787          | 1.0      |
| 0.0346        | 36.0  | 36   | 0.1746          | 1.0      |
| 0.0346        | 37.0  | 37   | 0.1714          | 1.0      |
| 0.0346        | 38.0  | 38   | 0.1691          | 1.0      |
| 0.0346        | 39.0  | 39   | 0.1676          | 1.0      |
| 0.021         | 40.0  | 40   | 0.1669          | 1.0      |


### Framework versions

- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2