See axolotl config
axolotl version: 0.4.1
base_model: lordspline/mergestein
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
chat_template: chatml
datasets:
- path: lordspline/scidata
type: sharegpt
conversation: chatml
- path: lordspline/wizard_v2_196k_unfiltered
type: sharegpt
conversation: chatml
- path: lordspline/ultrainteract
type: sharegpt
conversation: chatml
dataset_prepared_path: last_run_prepared
val_set_size: 0.002
output_dir: ./mergestein
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
wandb_project: mergestein
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
hub_model_id: lordspline/mergestein
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.0001 # look
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: unsloth
gradient_checkpointing_kwargs:
use_reentrant: true # look
early_stopping_patience:
resume_from_checkpoint: # ./mergestein/checkpoint-8015
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 1
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 300
debug:
# deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
eos_token: "<|im_end|>"
pad_token: "<|end_of_text|>"
tokens:
- "<|im_start|>"
- "<|im_end|>"
mergestein
This model is a fine-tuned version of lordspline/mergestein on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2069
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4476 | 1.0 | 48435 | 1.2069 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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