See axolotl config
axolotl version: 0.4.1
base_model: mistralai/Mistral-7B-v0.3
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
strict: false
# dataset
datasets:
- path: BEE-spoke-data/sarcasm-scrolls
type: completion # format from earlier
field: text
val_set_size: 200
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
train_on_inputs: false
group_by_length: false
# WANDB
wandb_project: sarcasm-scrolls
wandb_entity: pszemraj
wandb_watch: gradients
wandb_name: Mistral-7B-v0.3-sarcasm-scrolls-v2a
hub_model_id: pszemraj/Mistral-7B-v0.3-sarcasm-scrolls-v2
hub_strategy: every_save
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_torch_fused # paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-5
load_in_8bit: false
load_in_4bit: false
bf16: true
tf32: true
torch_compile: true
torch_compile_backend: inductor # Optional[str]
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
logging_steps: 3
xformers_attention:
flash_attention: true
warmup_steps: 20
# hyperparams for freq of evals, saving, etc
evals_per_epoch: 4
saves_per_epoch: 4
save_safetensors: true
save_total_limit: 1 # Checkpoints saved at a time
output_dir: ./output-axolotl/output-model-chaz
resume_from_checkpoint:
deepspeed:
weight_decay: 0.06
special_tokens:
Mistral-7B-v0.3-sarcasm-scrolls-v2
Model description
This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the BEE-spoke-data/sarcasm-scrolls dataset. It achieves the following results on the evaluation set:
- Loss: 2.3333
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0075 | 1 | 2.3935 |
2.3672 | 0.2548 | 34 | 2.3638 |
2.3751 | 0.5096 | 68 | 2.3499 |
2.308 | 0.7644 | 102 | 2.3238 |
2.2672 | 1.0035 | 136 | 2.3027 |
1.702 | 1.2583 | 170 | 2.3449 |
1.7456 | 1.5131 | 204 | 2.3370 |
1.7004 | 1.7679 | 238 | 2.3333 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.1+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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