🚀 AdamGrzesik/Samantha-PL-AG-Mistral-7B-v0.2
This model is a fine - tuned version of alpindale/Mistral-7B-v0.2-hf on the Samanta-PL-AG-axolotl dataset, offering enhanced performance in relevant tasks.
See axolotl config
axolotl version: 0.4.0
base_model: alpindale/Mistral-7B-v0.2-hf
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: /workspace/datasets/Samantha-PL-AG-axolotl.json
type: sharegpt
chat_template: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: /workspace/Samantha
sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 3
num_epochs: 4
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.000005
optimizer: adamw_bnb_8bit
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
eval_steps: 73
eval_table_size:
eval_table_max_new_tokens:
eval_sample_packing: false
saves_per_epoch:
save_steps: 73
save_total_limit: 2
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
eos_token: "<|im_end|>"
tokens:
- "<|im_start|>"
📚 Documentation
Model Information
| Property |
Details |
| Base Model |
alpindale/Mistral-7B-v0.2-hf |
| Model Type |
MistralForCausalLM |
| Tokenizer Type |
LlamaTokenizer |
| Is Mistral Derived Model |
true |
Training Hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi - GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 48
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
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Transformers