---
base_model: Qwen/Qwen-14B
tags:
- generated_from_trainer
datasets:
- jeopardy
model-index:
- name: final_jeopardy
  results: []
---

<!-- 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. -->

# final_jeopardy

This model is a fine-tuned version of [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) on the jeopardy dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3619

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.01
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0584        | 0.02  | 100  | 2.6536          |
| 2.6474        | 0.04  | 200  | 2.5669          |
| 2.5729        | 0.06  | 300  | 2.5225          |
| 2.5364        | 0.08  | 400  | 2.5054          |
| 2.4918        | 0.1   | 500  | 2.4876          |
| 2.502         | 0.12  | 600  | 2.4734          |
| 2.4993        | 0.14  | 700  | 2.4651          |
| 2.4982        | 0.16  | 800  | 2.4514          |
| 2.4676        | 0.18  | 900  | 2.4419          |
| 2.4414        | 0.2   | 1000 | 2.4396          |
| 2.4656        | 0.22  | 1100 | 2.4292          |
| 2.4795        | 0.24  | 1200 | 2.4250          |
| 2.4341        | 0.26  | 1300 | 2.4228          |
| 2.4276        | 0.28  | 1400 | 2.4157          |
| 2.4297        | 0.3   | 1500 | 2.4105          |
| 2.4617        | 0.32  | 1600 | 2.4084          |
| 2.4431        | 0.34  | 1700 | 2.4016          |
| 2.4037        | 0.36  | 1800 | 2.4002          |
| 2.4289        | 0.38  | 1900 | 2.3984          |
| 2.4351        | 0.4   | 2000 | 2.3922          |
| 2.3931        | 0.42  | 2100 | 2.3920          |
| 2.4253        | 0.44  | 2200 | 2.3892          |
| 2.4507        | 0.46  | 2300 | 2.3856          |
| 2.4063        | 0.48  | 2400 | 2.3846          |
| 2.4253        | 0.5   | 2500 | 2.3825          |
| 2.3948        | 0.52  | 2600 | 2.3778          |
| 2.3839        | 0.54  | 2700 | 2.3781          |
| 2.4304        | 0.56  | 2800 | 2.3799          |
| 2.4458        | 0.58  | 2900 | 2.3723          |
| 2.4051        | 0.6   | 3000 | 2.3733          |
| 2.3984        | 0.62  | 3100 | 2.3713          |
| 2.3886        | 0.64  | 3200 | 2.3702          |
| 2.3625        | 0.66  | 3300 | 2.3717          |
| 2.3745        | 0.68  | 3400 | 2.3676          |
| 2.4168        | 0.7   | 3500 | 2.3665          |
| 2.3761        | 0.72  | 3600 | 2.3669          |
| 2.379         | 0.74  | 3700 | 2.3662          |
| 2.3801        | 0.76  | 3800 | 2.3642          |
| 2.3817        | 0.78  | 3900 | 2.3640          |
| 2.4002        | 0.8   | 4000 | 2.3645          |
| 2.3989        | 0.82  | 4100 | 2.3635          |
| 2.3916        | 0.84  | 4200 | 2.3629          |
| 2.4045        | 0.86  | 4300 | 2.3624          |
| 2.3919        | 0.88  | 4400 | 2.3626          |
| 2.3943        | 0.9   | 4500 | 2.3626          |
| 2.3896        | 0.92  | 4600 | 2.3616          |
| 2.3518        | 0.94  | 4700 | 2.3621          |
| 2.41          | 0.96  | 4800 | 2.3616          |
| 2.3782        | 0.98  | 4900 | 2.3621          |
| 2.3589        | 1.0   | 5000 | 2.3619          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.1.0
- Datasets 2.14.7
- Tokenizers 0.13.3