File size: 1,496 Bytes
451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 ad10505 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 451b743 748f945 ad10505 451b743 748f945 451b743 748f945 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
library_name: transformers
base_model: ccore/getcode-v2
tags:
- generated_from_trainer
model-index:
- name: getcode-v2
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. -->
# getcode-v2
This model is a fine-tuned version of [ccore/getcode-v2](https://huggingface.co/ccore/getcode-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8979
## 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: 32
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9081 | 1.0 | 1361 | 0.9017 |
| 0.8947 | 1.9990 | 2720 | 0.8979 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|