metadata
base_model: bigcode/starcoderbase-1b
library_name: peft
license: bigcode-openrail-m
tags:
- generated_from_trainer
model-index:
- name: peft-starcoder-finetuned
results: []
peft-starcoder-finetuned
This model is a fine-tuned version of bigcode/starcoderbase-1b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8901
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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 20
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0733 | 0.1631 | 20 | 0.9622 |
| 1.0649 | 0.3262 | 40 | 0.9528 |
| 1.0324 | 0.4893 | 60 | 0.9462 |
| 1.0216 | 0.6524 | 80 | 0.9424 |
| 1.0067 | 0.8155 | 100 | 0.9368 |
| 0.9977 | 0.9786 | 120 | 0.9329 |
| 0.97 | 1.1458 | 140 | 0.9302 |
| 0.9085 | 1.3089 | 160 | 0.9279 |
| 0.934 | 1.4720 | 180 | 0.9233 |
| 1.0061 | 1.6351 | 200 | 0.9184 |
| 0.9564 | 1.7982 | 220 | 0.9165 |
| 0.9738 | 1.9613 | 240 | 0.9126 |
| 0.8864 | 2.1284 | 260 | 0.9114 |
| 0.9144 | 2.2915 | 280 | 0.9113 |
| 0.9443 | 2.4546 | 300 | 0.9098 |
| 0.9444 | 2.6177 | 320 | 0.9083 |
| 0.887 | 2.7808 | 340 | 0.9058 |
| 0.9398 | 2.9439 | 360 | 0.9052 |
| 0.9015 | 3.1111 | 380 | 0.9031 |
| 0.8536 | 3.2742 | 400 | 0.9024 |
| 0.8765 | 3.4373 | 420 | 0.9002 |
| 0.9198 | 3.6004 | 440 | 0.8997 |
| 0.9468 | 3.7635 | 460 | 0.8989 |
| 0.8631 | 3.9266 | 480 | 0.8978 |
| 0.8777 | 4.0938 | 500 | 0.8977 |
| 0.9006 | 4.2569 | 520 | 0.8959 |
| 0.8768 | 4.4200 | 540 | 0.8957 |
| 0.8477 | 4.5831 | 560 | 0.8951 |
| 0.9061 | 4.7462 | 580 | 0.8937 |
| 0.8837 | 4.9093 | 600 | 0.8930 |
| 0.8402 | 5.0765 | 620 | 0.8939 |
| 0.8608 | 5.2396 | 640 | 0.8931 |
| 0.879 | 5.4027 | 660 | 0.8928 |
| 0.8562 | 5.5657 | 680 | 0.8922 |
| 0.8776 | 5.7288 | 700 | 0.8913 |
| 0.8464 | 5.8919 | 720 | 0.8910 |
| 0.8528 | 6.0591 | 740 | 0.8914 |
| 0.8538 | 6.2222 | 760 | 0.8910 |
| 0.8844 | 6.3853 | 780 | 0.8905 |
| 0.8652 | 6.5484 | 800 | 0.8906 |
| 0.8443 | 6.7115 | 820 | 0.8905 |
| 0.8546 | 6.8746 | 840 | 0.8899 |
| 0.8094 | 7.0418 | 860 | 0.8904 |
| 0.863 | 7.2049 | 880 | 0.8899 |
| 0.8642 | 7.3680 | 900 | 0.8902 |
| 0.8413 | 7.5311 | 920 | 0.8901 |
| 0.8119 | 7.6942 | 940 | 0.8903 |
| 0.8909 | 7.8573 | 960 | 0.8901 |
| 0.8516 | 8.0245 | 980 | 0.8900 |
| 0.8834 | 8.1876 | 1000 | 0.8901 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3