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deepseek_coder_v2 – AI Model by johnnychang4 | AlphaNeural AI
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deepseek_coder_v2
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deepseek_coder_v2
This model is a fine-tuned version of
deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1922
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
0.4005
0.1613
5
0.3098
0.2848
0.3226
10
0.2342
0.2249
0.4839
15
0.2092
0.2221
0.6452
20
0.2001
0.2141
0.8065
25
0.1949
0.2094
0.9677
30
0.1922
Framework versions
PEFT 0.11.1
Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
