See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: Qwen/Qwen2.5-0.5B
bf16: auto
datasets:
- data_files:
- e7d5bcb285c8a077_train_data.json
ds_type: json
format: custom
path: e7d5bcb285c8a077_train_data.json
type:
field: null
field_input: disorder
field_instruction: input
field_output: dssp3
field_system: null
format: null
no_input_format: null
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_sample_packing: false
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: FatCat87/6201afaa-a647-4d6e-b7ef-21dbf1764a57
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 2
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: ./outputs/out
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
seed: 701
sequence_len: 4096
special_tokens: null
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0.1
wandb_entity: fatcat87-taopanda
wandb_log_model: null
wandb_mode: online
wandb_name: 6201afaa-a647-4d6e-b7ef-21dbf1764a57
wandb_project: subnet56
wandb_runid: 6201afaa-a647-4d6e-b7ef-21dbf1764a57
wandb_watch: null
warmup_ratio: 0.05
weight_decay: 0.0
xformers_attention: null
6201afaa-a647-4d6e-b7ef-21dbf1764a57
This model is a fine-tuned version of Qwen/Qwen2.5-0.5B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1313
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 701
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 8
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.951 | 0.0051 | 1 | 1.9665 |
1.1794 | 0.2506 | 49 | 1.1707 |
1.124 | 0.5013 | 98 | 1.1384 |
1.1442 | 0.7519 | 147 | 1.1313 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for FatCat87/6201afaa-a647-4d6e-b7ef-21dbf1764a57
Base model
Qwen/Qwen2.5-0.5B