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---
tags:
- generated_from_trainer
model-index:
- name: codellama-7b-humaneval-java-fim
results: []
library_name: peft
---
<!-- 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. -->
# codellama-7b-humaneval-java-fim
This model was trained from scratch on an [this](https://huggingface.co/datasets/sarthak247/humaneval-java-fixed) dataset for FIM task.
It achieves the following results on the evaluation set:
- Loss: 0.6155
## Model description
Codellama-7b model trained for FIM on Java code dataset.
## Intended uses & limitations
Bleh
## Training and evaluation data
Dataset mentioned above
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6594 | 0.05 | 100 | 0.6927 |
| 0.6701 | 0.1 | 200 | 0.6784 |
| 0.6329 | 0.15 | 300 | 0.6690 |
| 0.6361 | 0.2 | 400 | 0.6629 |
| 0.5964 | 0.25 | 500 | 0.6545 |
| 0.6247 | 0.3 | 600 | 0.6461 |
| 0.6146 | 0.35 | 700 | 0.6407 |
| 0.5892 | 0.4 | 800 | 0.6364 |
| 0.5916 | 0.45 | 900 | 0.6308 |
| 0.6069 | 0.5 | 1000 | 0.6267 |
| 0.5804 | 0.55 | 1100 | 0.6242 |
| 0.5793 | 0.6 | 1200 | 0.6212 |
| 0.5836 | 0.65 | 1300 | 0.6195 |
| 0.5839 | 0.7 | 1400 | 0.6174 |
| 0.597 | 0.75 | 1500 | 0.6162 |
| 0.6042 | 0.8 | 1600 | 0.6158 |
| 0.5777 | 0.85 | 1700 | 0.6155 |
| 0.5683 | 0.9 | 1800 | 0.6155 |
| 0.5613 | 0.95 | 1900 | 0.6155 |
| 0.5597 | 1.0 | 2000 | 0.6155 |
### Framework versions
- PEFT 0.5.0
- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.14.1
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