---
library_name: transformers
base_model: bowphs/pythia-70m-multi
tags:
- generated_from_trainer
datasets:
- allenai/c4
metrics:
- accuracy
model-index:
- name: c4-model
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: allenai/c4 en
      type: allenai/c4
      args: en
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.3716248289345064
---

<!-- 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. -->

# c4-model

This model is a fine-tuned version of [bowphs/pythia-70m-multi](https://huggingface.co/bowphs/pythia-70m-multi) on the allenai/c4 en dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5532
- Accuracy: 0.3716

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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
- training_steps: 30000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| No log        | 0.0000 | 1     | 10.7029         | 0.0164   |
| No log        | 0.0001 | 2     | 10.5331         | 0.0496   |
| No log        | 0.0001 | 4     | 10.3022         | 0.0533   |
| No log        | 0.0003 | 8     | 10.0235         | 0.0536   |
| No log        | 0.0005 | 16    | 9.6536          | 0.0635   |
| No log        | 0.0011 | 32    | 9.0284          | 0.0759   |
| No log        | 0.0021 | 64    | 8.0249          | 0.0832   |
| No log        | 0.0043 | 128   | 6.9172          | 0.1129   |
| No log        | 0.0085 | 256   | 6.1629          | 0.1558   |
| No log        | 0.0171 | 512   | 5.5805          | 0.1817   |
| No log        | 0.0341 | 1024  | 5.1235          | 0.2028   |
| 5.4529        | 0.0667 | 2000  | 4.7613          | 0.2264   |
| 5.4529        | 0.0683 | 2048  | 4.7481          | 0.2281   |
| 4.5765        | 0.1333 | 4000  | 4.4123          | 0.2610   |
| 4.5765        | 0.1365 | 4096  | 4.4043          | 0.2625   |
| 4.3252        | 0.2    | 6000  | 4.2221          | 0.2827   |
| 4.146         | 0.2667 | 8000  | 4.0350          | 0.3098   |
| 4.146         | 0.2731 | 8192  | 4.0134          | 0.3129   |
| 3.9652        | 0.3333 | 10000 | 3.8860          | 0.3304   |
| 3.8441        | 0.4    | 12000 | 3.8005          | 0.3418   |
| 3.7739        | 0.4667 | 14000 | 3.7315          | 0.3503   |
| 3.72          | 0.5333 | 16000 | 3.6880          | 0.3553   |
| 3.72          | 0.5461 | 16384 | 3.6777          | 0.3564   |
| 3.6718        | 0.6    | 18000 | 3.6533          | 0.3593   |
| 3.6527        | 0.6667 | 20000 | 3.6212          | 0.3633   |
| 3.6201        | 0.7333 | 22000 | 3.5985          | 0.3660   |
| 3.593         | 0.8    | 24000 | 3.5819          | 0.3679   |
| 3.5857        | 0.8667 | 26000 | 3.5683          | 0.3697   |
| 3.5801        | 0.9333 | 28000 | 3.5582          | 0.3711   |
| 3.5649        | 1.0    | 30000 | 3.5532          | 0.3716   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0