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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: ai21labs/Jamba-v0.1
model-index:
- name: out
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: ai21labs/Jamba-v0.1
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: chargoddard/Open-Platypus-Chat
type: sharegpt
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.01
output_dir: ./out
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false
use_wandb: true
wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_name: Jambatypus-v0.1
wandb_log_model:
adapter: qlora
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
low_cpu_mem_usage: true
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 4
save_total_limit: 2
debug:
deepspeed:
weight_decay: 0.0
special_tokens:
```
</details><br>
# out
This model is a fine-tuned version of [ai21labs/Jamba-v0.1](https://huggingface.co/ai21labs/Jamba-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9651
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6274 | 0.01 | 1 | 1.0298 |
| 0.4403 | 0.25 | 42 | 0.9768 |
| 0.4417 | 0.5 | 84 | 0.9675 |
| 0.4451 | 0.75 | 126 | 0.9652 |
| 0.4616 | 1.0 | 168 | 0.9651 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.0 |