---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-Nemo-Instruct-2407
tags:
- axolotl
- generated_from_trainer
<!-- datasets:
- ./train_data.jsonl-->
model-index:
- name: linabot
  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.8.0`
```yaml
base_model: mistralai/Mistral-Nemo-Instruct-2407
model_type: MistralForCausalLM
hub_model_id: Alignment-Lab-AI/linabot
strict: false
chat_template: tokenizer_default
plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_layer_norm: true
liger_fused_linear_cross_entropy: true
datasets:
  - path: "./train_data.jsonl"
    type: chat_template
    field_messages: messages
    message_property_mappings:
      role: role
      content: content
    roles_to_train: ['assistant']
    train_on_eos: turn

learning_rate: 2e-5
lr_scheduler: cosine
weight_decay: 0.03
warmup_steps: 450
dataset_prepared_path:
val_set_size: 0.2
output_dir: ./outputs/out

sequence_len: 10400
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: true

wandb_project: linabot
wandb_entity:
wandb_watch: all
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 4
num_epochs: 5
optimizer: adalomo
lr_scheduler: cosine
learning_rate: 0.0002024
flash_attention: true
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
torch_compile_mode: "max-autotune"
bf16: auto
tf32: false

gradient_checkpointing: true
resume_from_checkpoint:
logging_steps: 1

evals_per_epoch: 8
saves_per_epoch: 1
weight_decay: 0.03
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  pad_token: "<pad>"

```

</details><br>

# linabot

This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the ./train_data.jsonl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4157

## 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: 0.0002024
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adalomo and the args are:
No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 450
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4415        | 0.0083 | 1    | 0.5382          |
| 0.4958        | 0.125  | 15   | 0.5380          |
| 0.371         | 0.25   | 30   | 0.5371          |
| 0.4364        | 0.375  | 45   | 0.5347          |
| 0.3777        | 0.5    | 60   | 0.5309          |
| 0.3962        | 0.625  | 75   | 0.5244          |
| 0.3341        | 0.75   | 90   | 0.5168          |
| 0.3259        | 0.875  | 105  | 0.5070          |
| 0.3238        | 1.0    | 120  | 0.4966          |
| 0.36          | 1.125  | 135  | 0.4866          |
| 0.264         | 1.25   | 150  | 0.4793          |
| 0.3319        | 1.375  | 165  | 0.4714          |
| 0.3731        | 1.5    | 180  | 0.4641          |
| 0.325         | 1.625  | 195  | 0.4581          |
| 0.3477        | 1.75   | 210  | 0.4526          |
| 0.2851        | 1.875  | 225  | 0.4481          |
| 0.2732        | 2.0    | 240  | 0.4416          |
| 0.3367        | 2.125  | 255  | 0.4388          |
| 0.2605        | 2.25   | 270  | 0.4366          |
| 0.2725        | 2.375  | 285  | 0.4333          |
| 0.3374        | 2.5    | 300  | 0.4291          |
| 0.275         | 2.625  | 315  | 0.4250          |
| 0.1803        | 2.75   | 330  | 0.4214          |
| 0.3441        | 2.875  | 345  | 0.4189          |
| 0.1505        | 3.0    | 360  | 0.4172          |
| 0.2216        | 3.125  | 375  | 0.4186          |
| 0.1833        | 3.25   | 390  | 0.4185          |
| 0.2586        | 3.375  | 405  | 0.4153          |
| 0.1754        | 3.5    | 420  | 0.4152          |
| 0.2272        | 3.625  | 435  | 0.4136          |
| 0.174         | 3.75   | 450  | 0.4129          |
| 0.1794        | 3.875  | 465  | 0.4074          |
| 0.1779        | 4.0    | 480  | 0.4086          |
| 0.1752        | 4.125  | 495  | 0.4164          |
| 0.1745        | 4.25   | 510  | 0.4173          |
| 0.1314        | 4.375  | 525  | 0.4158          |
| 0.1923        | 4.5    | 540  | 0.4155          |
| 0.1848        | 4.625  | 555  | 0.4156          |
| 0.1185        | 4.75   | 570  | 0.4155          |
| 0.2255        | 4.875  | 585  | 0.4153          |
| 0.1841        | 5.0    | 600  | 0.4157          |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1