metadata
license: other
base_model: deepseek-ai/deepseek-coder-6.7b-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
model-index:
- name: >-
deepseek-coder-6.7b-instruct_Fi__translations_size_104_epochs_10_2024-06-21_23-44-44_3557640
results: []
deepseek-coder-6.7b-instruct_Fi__translations_size_104_epochs_10_2024-06-21_23-44-44_3557640
This model is a fine-tuned version of deepseek-ai/deepseek-coder-6.7b-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9391
- Accuracy: 0.027
- Chrf: 0.526
- Bleu: 0.433
- Sacrebleu: 0.4
- Rouge1: 0.512
- Rouge2: 0.258
- Rougel: 0.471
- Rougelsum: 0.507
- Meteor: 0.438
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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 3407
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 104
- training_steps: 1040
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf | Bleu | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.1525 | 4.0 | 104 | 1.1253 | 0.014 | 0.725 | 0.595 | 0.6 | 0.702 | 0.477 | 0.625 | 0.693 | 0.513 |
0.1027 | 8.0 | 208 | 1.2219 | 0.014 | 0.711 | 0.58 | 0.6 | 0.684 | 0.45 | 0.611 | 0.673 | 0.51 |
0.1307 | 12.0 | 312 | 1.3506 | 0.025 | 0.709 | 0.606 | 0.6 | 0.689 | 0.472 | 0.616 | 0.679 | 0.545 |
1.0101 | 16.0 | 416 | 1.6526 | 0.017 | 0.706 | 0.614 | 0.6 | 0.696 | 0.494 | 0.629 | 0.687 | 0.532 |
0.177 | 20.0 | 520 | 2.0077 | 0.028 | 0.663 | 0.558 | 0.6 | 0.659 | 0.439 | 0.594 | 0.653 | 0.46 |
0.2181 | 24.0 | 624 | 2.4044 | 0.02 | 0.615 | 0.507 | 0.5 | 0.623 | 0.393 | 0.565 | 0.617 | 0.474 |
0.9954 | 28.0 | 728 | 2.5812 | 0.025 | 0.585 | 0.483 | 0.5 | 0.579 | 0.329 | 0.523 | 0.569 | 0.452 |
0.28 | 32.0 | 832 | 2.8603 | 0.034 | 0.548 | 0.462 | 0.5 | 0.543 | 0.299 | 0.499 | 0.538 | 0.424 |
0.3616 | 36.0 | 936 | 2.9194 | 0.031 | 0.532 | 0.436 | 0.4 | 0.522 | 0.266 | 0.476 | 0.516 | 0.437 |
0.3022 | 40.0 | 1040 | 2.9391 | 0.027 | 0.526 | 0.433 | 0.4 | 0.512 | 0.258 | 0.471 | 0.507 | 0.438 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2