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Jambert

Text Generation
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jamba
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4-bit precision
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Jambert
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---
library_name: peft
tags:
- generated_from_trainer
base_model: jamba
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: jamba
trust_remote_code: true

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: scikit_admin_result.json
    ds_type: json
    type: sharegpt
    conversation: chatml
dataset_prepared_path:
val_set_size: 0.01
output_dir: ./out

sequence_len: 6000
sample_packing: true
pad_to_sequence_len: false
eval_sample_packing: true

use_wandb: false

adapter: qlora
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true

low_cpu_mem_usage: true
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 2
optimizer: paged_adamw_8bit
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: 2
saves_per_epoch: 2
debug:
weight_decay: 0.0
special_tokens:

```

</details><br>

# out

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2356

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4337        | 0.0   | 1    | 0.3783          |
| 0.2537        | 0.5   | 103  | 0.2345          |
| 0.2161        | 1.0   | 206  | 0.2258          |
| 0.1821        | 1.47  | 309  | 0.2356          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0