joseagmz/mistral-7B-PsychiatryCaseNotes-epochs-1-lr-000002
016
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<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>
axolotl version: 0.4.0
base_model: mistralai/Mistral-7B-v0.1
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: utrgvseniorproject/PsychiatryCaseNotes
type: completion
dataset_prepared_path: /home/josegomez15/med-llm/last_run_prepared
val_set_size: 0.05
output_dir: ./mistral-7B-PsychiatryCaseNotes-epochs-1-lr-000002
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true
wandb_project: mistral-7B-PsychiatryCaseNotes
wandb_entity: utrgvmedai
wandb_watch:
wandb_name: mistral-7B-PsychiatryCaseNotes-epochs-1-lr-000002
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000002
train_on_inputs: True # make sure you have this on True
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
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
eval_sample_packing:
saves_per_epoch: 1
debug:
deepspeed: /home/josegomez15/axolotl/deepspeed_configs/zero2.json
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
</details><br>
mistral-7B-PsychiatryCaseNotes-epochs-1-lr-000002
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8674
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-06
- trainbatchsize: 1
- evalbatchsize: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- totaltrainbatch_size: 8
- totalevalbatch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 100
- num_epochs: 1
Training results
Framework versions
- Transformers 4.38.0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.0