---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-Nemo-Instruct-2407
tags:
- axolotl
- generated_from_trainer
datasets:
- linabot/train_data
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: linabot/train_data
    type: chat_template
    field_messages: messages
    message_property_mappings:
      role: role
      content: content
    roles_to_train: ['assistant', 'user']
    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 linabot/train_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0558

## 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 OptimizerNames.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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.526         | 0.0083 | 1    | 1.5474          |
| 1.5934        | 0.125  | 15   | 1.5472          |
| 1.5242        | 0.25   | 30   | 1.5454          |
| 1.5296        | 0.375  | 45   | 1.5408          |
| 1.5087        | 0.5    | 60   | 1.5322          |
| 1.486         | 0.625  | 75   | 1.5188          |
| 1.4314        | 0.75   | 90   | 1.5005          |
| 1.4311        | 0.875  | 105  | 1.4782          |
| 1.4532        | 1.0    | 120  | 1.4513          |
| 1.4215        | 1.125  | 135  | 1.4198          |
| 1.3248        | 1.25   | 150  | 1.3825          |
| 1.2697        | 1.375  | 165  | 1.3386          |
| 1.3281        | 1.5    | 180  | 1.2880          |
| 1.2428        | 1.625  | 195  | 1.2296          |
| 1.1533        | 1.75   | 210  | 1.1596          |
| 1.1038        | 1.875  | 225  | 1.0747          |
| 1.0226        | 2.0    | 240  | 0.9723          |
| 0.8858        | 2.125  | 255  | 0.8467          |
| 0.6762        | 2.25   | 270  | 0.7047          |
| 0.6433        | 2.375  | 285  | 0.5626          |
| 0.4017        | 2.5    | 300  | 0.4283          |
| 0.2875        | 2.625  | 315  | 0.3072          |
| 0.2244        | 2.75   | 330  | 0.2161          |
| 0.1445        | 2.875  | 345  | 0.1572          |
| 0.0898        | 3.0    | 360  | 0.1192          |
| 0.0666        | 3.125  | 375  | 0.0991          |
| 0.0605        | 3.25   | 390  | 0.0855          |
| 0.0457        | 3.375  | 405  | 0.0757          |
| 0.052         | 3.5    | 420  | 0.0700          |
| 0.0634        | 3.625  | 435  | 0.0658          |
| 0.0364        | 3.75   | 450  | 0.0623          |
| 0.045         | 3.875  | 465  | 0.0601          |
| 0.0395        | 4.0    | 480  | 0.0582          |
| 0.0558        | 4.125  | 495  | 0.0573          |
| 0.0468        | 4.25   | 510  | 0.0566          |
| 0.0399        | 4.375  | 525  | 0.0562          |
| 0.0337        | 4.5    | 540  | 0.0560          |
| 0.0413        | 4.625  | 555  | 0.0559          |
| 0.0318        | 4.75   | 570  | 0.0558          |
| 0.0435        | 4.875  | 585  | 0.0558          |
| 0.0445        | 5.0    | 600  | 0.0558          |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1