metadata
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- axolotl
- generated_from_trainer
model-index:
- name: deepseek-coder-1.3b-typescript
results: []
datasets:
- bigcode/the-stack-dedup
widget:
- text: |-
class Person {
constructor(public name:
example_title: class
- text: function quickSort
example_title: function
[CodeGPT.co] | [🦙 Ollama] | [Discord] | [VSCode Extension]
See axolotl config
axolotl version: 0.3.0
base_model: deepseek-ai/deepseek-coder-1.3b-base
model_type: AutoModelForCausalLM
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: CodeGPTPlus/typescript-0-500000-seq1024
type: completion
field: text
val_set_size: 0.001
output_dir: ./fft-out
sequence_len: 1024
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
lora_modules_to_save:
wandb_project: deepseek_1.3_fft
wandb_entity:
wandb_watch:
wandb_name: aws_a10g
wandb_log_model: end
gradient_accumulation_steps: 2
micro_batch_size: 20
num_epochs: 1
optimizer: adamw_bnb_8bit
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 0.000001
max_grad_norm: 1.0
weight_decay: 0.1
lr_scheduler: cosine
learning_rate: 0.00002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
hub_model_id: CodeGPTPlus/deepseek_coder_1.3b_typescript
hub_strategy: every_save
warmup_ratio: 0.01
evals_per_epoch: 20
saves_per_epoch: 3
debug:
deepspeed:
fsdp:
fsdp_config:
special_tokens:
bos_token: "<｜begin▁of▁sentence｜>"
eos_token: "<｜end▁of▁sentence｜>"
pad_token: "<｜end▁of▁sentence｜>"
deepseek-coder-1.3b-typescript
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on the the-stack dataset, using 0.5B of tokens of typescript only. It achieves the following results on the evaluation set:
- Loss: 0.7681
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 261
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0745 | 0.0 | 1 | 0.8681 |
| 1.2267 | 0.05 | 1308 | 0.8130 |
| 1.1594 | 0.1 | 2616 | 0.8018 |
| 0.7674 | 0.15 | 3924 | 0.7942 |
| 0.6443 | 0.2 | 5232 | 0.7889 |
| 0.9155 | 0.25 | 6540 | 0.7847 |
| 0.7501 | 0.3 | 7848 | 0.7819 |
| 0.8835 | 0.35 | 9156 | 0.7792 |
| 0.7261 | 0.4 | 10464 | 0.7769 |
| 0.9746 | 0.45 | 11772 | 0.7748 |
| 0.6884 | 0.5 | 13080 | 0.7734 |
| 0.6104 | 0.55 | 14388 | 0.7722 |
| 0.8876 | 0.6 | 15696 | 0.7710 |
| 0.9567 | 0.65 | 17004 | 0.7703 |
| 0.6915 | 0.7 | 18312 | 0.7696 |
| 0.8874 | 0.75 | 19620 | 0.7691 |
| 0.6124 | 0.8 | 20928 | 0.7686 |
| 0.8147 | 0.85 | 22236 | 0.7684 |
| 0.8021 | 0.9 | 23544 | 0.7683 |
| 0.8665 | 0.95 | 24852 | 0.7681 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0