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---
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
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