---
library_name: peft
license: other
base_model: minpeter/HyperCLOVAX-SEED-Text-Instruct-3B-hf
tags:
- axolotl
- generated_from_trainer
datasets:
- minpeter/xlam-function-calling-60k-hermes
- minpeter/xlam-irrelevance-7.5k-qwen2.5-72b-distill-hermes
- minpeter/hermes-function-calling-v1-jsonl
- minpeter/hermes-function-calling-v1-jsonl
- minpeter/apigen-mt-5k-friendli
model-index:
- name: LoRA-HCX-3b-sf-xlam-01
results: []
---
---
## Model Test Score Comparison (BFCL)
| Test Item | tool Model Accuracy | base Model Accuracy | Score Difference (tool - base) |
| :---------------- | :-----------------: | :-----------------: | :----------------------------: |
| irrelevance | 0.8708 | 0.4333 | +0.4375 |
| multi_turn_base | 0.0350 | 0.0100 | +0.0250 |
| parallel_multiple | 0.7950 | 0.4750 | +0.3200 |
| parallel | 0.7900 | 0.5200 | +0.2700 |
| simple | 0.8375 | 0.7575 | +0.0800 |
| multiple | 0.8700 | 0.7650 | +0.1050 |
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
axolotl version: `0.10.0.dev0`
```yaml
base_model: minpeter/HyperCLOVAX-SEED-Text-Instruct-3B-hf
hub_model_id: minpeter/LoRA-HCX-3b-sf-xlam-01
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: minpeter/xlam-function-calling-60k-hermes
data_files:
- result.parquet
type: chat_template
roles_to_train: ["assistant"]
field_messages: conversations
message_property_mappings:
role: from
content: value
shards: 120
- path: minpeter/xlam-irrelevance-7.5k-qwen2.5-72b-distill-hermes
data_files:
- result.parquet
type: chat_template
roles_to_train: ["assistant"]
field_messages: conversations
message_property_mappings:
role: from
content: value
shards: 15
- path: minpeter/hermes-function-calling-v1-jsonl
data_files:
- func-calling-singleturn.jsonl
- func-calling.jsonl
type: chat_template
roles_to_train: ["assistant"]
field_messages: conversations
message_property_mappings:
role: from
content: value
shards: 3
- path: minpeter/hermes-function-calling-v1-jsonl
data_files:
- glaive-function-calling-5k.jsonl
type: chat_template
roles_to_train: ["assistant"]
field_messages: conversations
message_property_mappings:
role: from
content: value
shards: 5
- path: minpeter/apigen-mt-5k-friendli
data_files:
- train.jsonl
- test.jsonl
type: chat_template
roles_to_train: ["assistant"]
field_messages: messages
message_property_mappings:
role: role
content: content
shards: 10
chat_template: chatml
dataset_prepared_path: last_run_prepared
output_dir: ./output
adapter: lora
lora_model_dir:
sequence_len: 20000
pad_to_sequence_len: true
sample_packing: true
val_set_size: 0.05
eval_sample_packing: true
evals_per_epoch: 3
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: "axolotl"
wandb_entity: "kasfiekfs-e"
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
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
warmup_steps: 10
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<|im_start|>"
eos_token: "<|im_end|>"
pad_token: "<|endoftext|>"
```
# LoRA-HCX-3b-sf-xlam-01
This model is a fine-tuned version of [minpeter/HyperCLOVAX-SEED-Text-Instruct-3B-hf](https://huggingface.co/minpeter/HyperCLOVAX-SEED-Text-Instruct-3B-hf) on the minpeter/xlam-function-calling-60k-hermes, the minpeter/xlam-irrelevance-7.5k-qwen2.5-72b-distill-hermes, the minpeter/hermes-function-calling-v1-jsonl, the minpeter/hermes-function-calling-v1-jsonl and the minpeter/apigen-mt-5k-friendli datasets.
It achieves the following results on the evaluation set:
- Loss: 0.3609
## 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: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7577 | 0.0108 | 1 | 0.8759 |
| 0.3934 | 0.3333 | 31 | 0.4609 |
| 0.3151 | 0.6667 | 62 | 0.4033 |
| 0.4147 | 1.0 | 93 | 0.3788 |
| 0.3355 | 1.3333 | 124 | 0.3674 |
| 0.3675 | 1.6667 | 155 | 0.3620 |
| 0.3235 | 2.0 | 186 | 0.3609 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1