---
library_name: peft
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- generated_from_trainer
model-index:
- name: lemexp-task1-v2-lemma_object_small_nodefs-deepseek-coder-1.3b-base-ddp-8lr-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. -->

# lemexp-task1-v2-lemma_object_small_nodefs-deepseek-coder-1.3b-base-ddp-8lr-v2

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2645

## 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: 0.0008
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- 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
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.6349        | 0.2001  | 720   | 0.5111          |
| 0.5017        | 0.4001  | 1440  | 0.4620          |
| 0.4349        | 0.6002  | 2160  | 0.4331          |
| 0.417         | 0.8002  | 2880  | 0.4095          |
| 0.3957        | 1.0003  | 3600  | 0.4012          |
| 0.3607        | 1.2003  | 4320  | 0.3890          |
| 0.3585        | 1.4004  | 5040  | 0.3751          |
| 0.3561        | 1.6004  | 5760  | 0.3749          |
| 0.3505        | 1.8005  | 6480  | 0.3672          |
| 0.3438        | 2.0006  | 7200  | 0.3510          |
| 0.323         | 2.2006  | 7920  | 0.3524          |
| 0.3172        | 2.4007  | 8640  | 0.3435          |
| 0.3133        | 2.6007  | 9360  | 0.3368          |
| 0.3125        | 2.8008  | 10080 | 0.3331          |
| 0.312         | 3.0008  | 10800 | 0.3309          |
| 0.2852        | 3.2009  | 11520 | 0.3303          |
| 0.2916        | 3.4009  | 12240 | 0.3187          |
| 0.2876        | 3.6010  | 12960 | 0.3235          |
| 0.2868        | 3.8011  | 13680 | 0.3209          |
| 0.287         | 4.0011  | 14400 | 0.3150          |
| 0.2582        | 4.2012  | 15120 | 0.3147          |
| 0.2678        | 4.4012  | 15840 | 0.3117          |
| 0.2625        | 4.6013  | 16560 | 0.3082          |
| 0.2683        | 4.8013  | 17280 | 0.3010          |
| 0.2597        | 5.0014  | 18000 | 0.3030          |
| 0.2402        | 5.2014  | 18720 | 0.3017          |
| 0.2405        | 5.4015  | 19440 | 0.2975          |
| 0.2441        | 5.6016  | 20160 | 0.2950          |
| 0.2443        | 5.8016  | 20880 | 0.2945          |
| 0.2383        | 6.0017  | 21600 | 0.2912          |
| 0.2208        | 6.2017  | 22320 | 0.2862          |
| 0.2233        | 6.4018  | 23040 | 0.2856          |
| 0.2222        | 6.6018  | 23760 | 0.2818          |
| 0.2208        | 6.8019  | 24480 | 0.2808          |
| 0.2214        | 7.0019  | 25200 | 0.2786          |
| 0.2039        | 7.2020  | 25920 | 0.2844          |
| 0.1996        | 7.4021  | 26640 | 0.2802          |
| 0.1996        | 7.6021  | 27360 | 0.2814          |
| 0.2003        | 7.8022  | 28080 | 0.2721          |
| 0.2047        | 8.0022  | 28800 | 0.2717          |
| 0.1801        | 8.2023  | 29520 | 0.2722          |
| 0.1771        | 8.4023  | 30240 | 0.2736          |
| 0.1814        | 8.6024  | 30960 | 0.2716          |
| 0.1781        | 8.8024  | 31680 | 0.2663          |
| 0.1812        | 9.0025  | 32400 | 0.2668          |
| 0.1584        | 9.2026  | 33120 | 0.2684          |
| 0.1578        | 9.4026  | 33840 | 0.2635          |
| 0.1627        | 9.6027  | 34560 | 0.2666          |
| 0.1612        | 9.8027  | 35280 | 0.2601          |
| 0.1576        | 10.0028 | 36000 | 0.2623          |
| 0.14          | 10.2028 | 36720 | 0.2660          |
| 0.1403        | 10.4029 | 37440 | 0.2619          |
| 0.1407        | 10.6029 | 38160 | 0.2592          |
| 0.1399        | 10.8030 | 38880 | 0.2594          |
| 0.1424        | 11.0031 | 39600 | 0.2599          |
| 0.1275        | 11.2031 | 40320 | 0.2703          |
| 0.1253        | 11.4032 | 41040 | 0.2662          |
| 0.1242        | 11.6032 | 41760 | 0.2641          |
| 0.1234        | 11.8033 | 42480 | 0.2645          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0