axolotl version: 0.4.1
base_model: Delta-Vector/Holland-4B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: NewEden/xlam-function-calling-60k-shareGPT
type: sharegpt
conversation: chatml
chat_template: chatml
val_set_size: 0.01
output_dir: ./outputs/out
adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
sequence_len: 8192
# sequence_len: 32768
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true
wandb_project: GnX Func Calling v2
wandb_entity:
wandb_watch:
wandb_name: Func Calling GnX v2
wandb_log_model:
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00002
weight_decay: 0.05
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
fsdp:
fsdp_config:
special_tokens:
pad_token: <|finetune_right_pad_id|>
outputs/out
This model is a fine-tuned version of Delta-Vector/Holland-4B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0359
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 8
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4049 | 0.0224 | 1 | 0.5064 |
| 0.0803 | 0.2462 | 11 | 0.0692 |
| 0.0279 | 0.4923 | 22 | 0.0404 |
| 0.0294 | 0.7385 | 33 | 0.0396 |
| 0.0346 | 0.9846 | 44 | 0.0365 |
| 0.0128 | 1.2189 | 55 | 0.0375 |
| 0.0241 | 1.4650 | 66 | 0.0375 |
| 0.0134 | 1.7112 | 77 | 0.0361 |
| 0.0133 | 1.9573 | 88 | 0.0359 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1