---
license: apache-2.0
base_model: EleutherAI/pythia-410m-deduped-v0
tags:
- generated_from_trainer
model-index:
- name: eleuter-foodie-test-2
  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. -->

# eleuter-foodie-test-2

This model is a fine-tuned version of [EleutherAI/pythia-410m-deduped-v0](https://huggingface.co/EleutherAI/pythia-410m-deduped-v0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3148

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3434        | 0.06  | 200  | 1.4594          |
| 1.2535        | 0.11  | 400  | 1.4383          |
| 1.2794        | 0.17  | 600  | 1.4265          |
| 1.2913        | 0.22  | 800  | 1.4185          |
| 1.2776        | 0.28  | 1000 | 1.4054          |
| 1.2929        | 0.34  | 1200 | 1.3950          |
| 1.2357        | 0.39  | 1400 | 1.3975          |
| 1.2235        | 0.45  | 1600 | 1.3886          |
| 1.2609        | 0.5   | 1800 | 1.3854          |
| 1.2002        | 0.56  | 2000 | 1.3774          |
| 1.2729        | 0.61  | 2200 | 1.3745          |
| 1.2143        | 0.67  | 2400 | 1.3680          |
| 1.2011        | 0.73  | 2600 | 1.3670          |
| 1.2697        | 0.78  | 2800 | 1.3625          |
| 1.2499        | 0.84  | 3000 | 1.3593          |
| 1.2409        | 0.89  | 3200 | 1.3536          |
| 1.2393        | 0.95  | 3400 | 1.3497          |
| 1.3622        | 1.01  | 3600 | 1.3411          |
| 1.2965        | 1.06  | 3800 | 1.3408          |
| 1.3515        | 1.12  | 4000 | 1.3366          |
| 1.3451        | 1.17  | 4200 | 1.3359          |
| 1.3427        | 1.23  | 4400 | 1.3343          |
| 1.3735        | 1.28  | 4600 | 1.3344          |
| 1.348         | 1.34  | 4800 | 1.3322          |
| 1.3536        | 1.4   | 5000 | 1.3315          |
| 1.284         | 1.45  | 5200 | 1.3281          |
| 1.2912        | 1.51  | 5400 | 1.3272          |
| 1.3119        | 1.56  | 5600 | 1.3261          |
| 1.3422        | 1.62  | 5800 | 1.3221          |
| 1.3139        | 1.68  | 6000 | 1.3201          |
| 1.3222        | 1.73  | 6200 | 1.3181          |
| 1.3038        | 1.79  | 6400 | 1.3181          |
| 1.296         | 1.84  | 6600 | 1.3169          |
| 1.3562        | 1.9   | 6800 | 1.3166          |
| 1.2887        | 1.95  | 7000 | 1.3148          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3