jeiku/Everything_v3_128_StableLM
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<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>
axolotl version: 0.3.0
base_model: stabilityai/stablelm-3b-4e1t
base_model_config: stabilityai/stablelm-3b-4e1t
trust_remote_code: true
model_type: AutoModelForCausalLM
tokenizer_type: GPTNeoXTokenizerFast
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: totally-not-an-llm/EverythingLM-data-V3
type: alpaca
dataset_prepared_path:
val_set_size: 0.005
output_dir: ./everything
adapter: qlora
sequence_len: 1024
sample_packing: false
pad_to_sequence_len: true
save_safetensors: false
lora_r: 128
lora_alpha: 256
lora_dropout: 0.05
lora_target_linear: false
lora_fan_in_fan_out:
lora_modules_to_save:
- embed_tokens
- lm_head
lora_target_modules:
- q_proj
- v_proj
gradient_accumulation_steps: 1
micro_batch_size: 16
num_epochs: 5
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.00005
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
warmup_steps: 10
evals_per_epoch: 1
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<|endoftext|>"
eos_token: "<|im_end|>"
unk_token: "<|endoftext|>"
tokens:
- "<|im_start|>"
- "<|im_end|>"
</details><br>
everything
This model is a fine-tuned version of stabilityai/stablelm-3b-4e1t on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8096
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- loadin8bit: False
- loadin4bit: True
- llmint8threshold: 6.0
- llmint8skip_modules: None
- llmint8enablefp32cpu_offload: False
- llmint8hasfp16weight: False
- bnb4bitquant_type: nf4
- bnb4bitusedoublequant: True
- bnb4bitcompute_dtype: bfloat16
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- trainbatchsize: 16
- evalbatchsize: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 10
- num_epochs: 5
Training results
Framework versions
- PEFT 0.7.0
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0