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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: llmTechChat-lora
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.3.0`
```yaml
base_model: mistralai/Mistral-7B-v0.1
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: true
load_in_4bit: false
strict: false
datasets:
- path: datasets/norobots_150/norobots_150
type: completion
- path: datasets/separated/bloke-separate
type: completion
- path: datasets/separated/kcpp-separate
type: completion
- path: datasets/separated/kcpp-support-separate
type: completion
- path: datasets/separated/st-chat-separate
type: completion
- path: datasets/separated/exllama2_readme.txt
type: completion
- path: datasets/separated/koboldcpp_readme.txt
type: completion
- path: datasets/separated/llama_readme.txt
type: completion
- path: datasets/separated/ooba_readme.txt
type: completion
- path: datasets/separated/sillytavern_readme.txt
type: completion
- path: datasets/separated/sillytavern_simple_setup_guide.txt
type: completion
- path: datasets/transformer_article.txt
type: completion
- path: datasets/lmg_thread.txt
type: completion
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./llmTechChat-lora
adapter: lora
lora_model_dir:
chat_template: chatml
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
lora_r: 128
lora_alpha: 64
lora_dropout: 0.20
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: llmTechChat
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0003
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
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
save_safetensors: true
```
</details><br>
# llmTechChat-lora
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9365
## 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
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3577 | 0.01 | 1 | 4.3261 |
| 2.0615 | 0.25 | 40 | 2.0476 |
| 1.9905 | 0.5 | 80 | 1.9691 |
| 1.8699 | 0.75 | 120 | 1.9344 |
| 1.9604 | 1.0 | 160 | 1.9111 |
| 1.7684 | 1.23 | 200 | 1.8978 |
| 1.7673 | 1.48 | 240 | 1.8809 |
| 1.7296 | 1.73 | 280 | 1.8630 |
| 1.7737 | 1.98 | 320 | 1.8479 |
| 1.5871 | 2.22 | 360 | 1.8883 |
| 1.5339 | 2.47 | 400 | 1.8761 |
| 1.5589 | 2.72 | 440 | 1.8657 |
| 1.5651 | 2.96 | 480 | 1.8590 |
| 1.3134 | 3.2 | 520 | 1.9497 |
| 1.3423 | 3.45 | 560 | 1.9406 |
| 1.3635 | 3.7 | 600 | 1.9362 |
| 1.3235 | 3.95 | 640 | 1.9365 |
### Framework versions
- PEFT 0.7.0
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0 |