Missing YAML mlflow

[l3utterfly]

Please check that this issue hasn't been reported before.

• [X] I searched previous Bug Reports didn't find any similar reports.

Expected Behavior

Works

Current behaviour

Installing from the instructions in the ReadMe.md, get this error when starting training:

mlflow.exceptions.MissingConfigException: Yaml file '/home/layla/src/axolotl/mlruns/0/meta.yaml' does not exist.

Steps to reproduce

1. Install from source
2. start training with any example

Config yaml

No response

Possible solution

No response

Which Operating Systems are you using?

• [X] Linux
• [ ] macOS
• [ ] Windows

Python Version

3.11

axolotl branch-commit

main

Acknowledgements

• [X] My issue title is concise, descriptive, and in title casing.
• [X] I have searched the existing issues to make sure this bug has not been reported yet.
• [X] I am using the latest version of axolotl.
• [X] I have provided enough information for the maintainers to reproduce and diagnose the issue.

[NanoCode012]

can you share config

[l3utterfly]

Here is the config:

base_model: /home/layla/src/text-generation-webui/models/Mistral-7B-v0.1
base_model_config: /home/layla/src/text-generation-webui/models/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: /data.jsonl
    ds_type: json # see other options below
    type: sharegpt
    conversation: vicuna_v1.1

dataset_prepared_path: last_run_prepared
val_set_size: 0.002
output_dir: ./out

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

wandb_project:
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0000005

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

warmup_ratio: 0.05
eval_steps: 0.1
eval_table_size:
eval_table_max_new_tokens: 128
eval_sample_packing: false
save_steps: 100
debug:
deepspeed: zero3_cpuoffload.json # multi-gpu only
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"