Jue Wang
init
cb70b64
---
license: apache-2.0
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
model-index:
- name: mixtral-lora-less-modules
results: []
---
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<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: true
strict: false
chat_template: inst
datasets:
- path: ./data/raw_format/tool_used_training.jsonl
type: sharegpt
conversation: mistral
- path: ./data/raw_format/tool_not_used_training.jsonl
type: sharegpt
conversation: mistral
- path: ./data/raw_format/no_tools_training.jsonl
type: sharegpt
conversation: mistral
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
output_dir: ./mixtral-lora-2-epochs-r64
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
lora_r: 64
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out:
hub_model_id: liuylhf/mixtral-lora-less-modules
hub_strategy: end
lora_target_modules:
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: function-call
wandb_name: mixtral-instruct-raw-data-v3
wandb_log_model: end
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.001
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
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
# evals_per_epoch: 20
eval_steps: 0.1
save_steps: 0.1
eval_table_size:
eval_max_new_tokens: 256
# saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 1.0
fsdp:
fsdp_config:
```
</details><br>
# mixtral-lora-less-modules
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1904
## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- 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=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2966 | 0.0 | 1 | 3.2222 |
| 0.1826 | 0.4 | 123 | 0.2012 |
| 0.1729 | 0.8 | 246 | 0.1925 |
| 0.1852 | 1.19 | 369 | 0.1913 |
| 0.1463 | 1.59 | 492 | 0.1857 |
| 0.1246 | 1.99 | 615 | 0.1840 |
| 0.1149 | 2.37 | 738 | 0.1872 |
| 0.076 | 2.77 | 861 | 0.1837 |
| 0.0763 | 3.15 | 984 | 0.1920 |
| 0.0906 | 3.56 | 1107 | 0.1904 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.0