Hugging Face's logo

kweinmeister
/
gemma-2-2b-it-dolly-15k

Text Generation
PEFT
Safetensors
gemma2
axolotl
Generated from Trainer
conversational
4-bit precision
bitsandbytes
Model card Files Community
gemma-2-2b-it-dolly-15k
File size: 3,525 Bytes 
a3f09db
 
 
 
 
 
 
 
 
 
023e185
 
 
a3f09db
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
 
---
library_name: peft
license: gemma
base_model: google/gemma-2-2b-it
tags:
- axolotl
- generated_from_trainer
model-index:
- name: gemma-2-2b-it-dolly-15k
  results: []
datasets:
- databricks/databricks-dolly-15k
pipeline_tag: text-generation
---

<!-- 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: `0.5.2`
```yaml
base_model: google/gemma-2-2b-it
hub_model_id: kweinmeister/gemma-2-2b-it-dolly-15k

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: databricks/databricks-dolly-15k
    type:
      field_instruction: instruction       
      field_input: context
      field_output: response
val_set_size: 0.05

sequence_len: 2048
sample_packing: true
eval_sample_packing: true
pad_to_sequence_len: true

adapter: qlora
lora_model_dir:
lora_r: 32
lora_alpha: 64
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: gemma-2-2b-it-dolly-15k
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero1.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
output_dir: "/mnt/disks/gcs/axolotl/runs/google--gemma-2-2b-it-20250101-144050/out/"
dataset_prepared_path: "/mnt/disks/gcs/axolotl/last_run_prepared"

```

</details><br>

# gemma-2-2b-it-dolly-15k

This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7389

## 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: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.7033        | 0.0061 | 1    | 5.5100          |
| 1.8197        | 0.2492 | 41   | 1.8752          |
| 1.6386        | 0.4985 | 82   | 1.7666          |
| 1.7346        | 0.7477 | 123  | 1.7436          |
| 1.7742        | 0.9970 | 164  | 1.7389          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3