|
--- |
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dataset_info: |
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features: |
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- name: output |
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dtype: string |
|
- name: instruction |
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dtype: string |
|
splits: |
|
- name: arithmetic.float2_train |
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num_bytes: 645500.3 |
|
num_examples: 19000 |
|
- name: arithmetic.float2_valid |
|
num_bytes: 33973.7 |
|
num_examples: 1000 |
|
- name: arithmetic.float3_train |
|
num_bytes: 1890863.85 |
|
num_examples: 47500 |
|
- name: arithmetic.float3_valid |
|
num_bytes: 99519.15 |
|
num_examples: 2500 |
|
- name: arithmetic.float34_train |
|
num_bytes: 9321513.05 |
|
num_examples: 218500 |
|
- name: arithmetic.float34_valid |
|
num_bytes: 490605.95 |
|
num_examples: 11500 |
|
- name: arithmetic.float4_train |
|
num_bytes: 21671996.6 |
|
num_examples: 475000 |
|
- name: arithmetic.float4_valid |
|
num_bytes: 1140631.4 |
|
num_examples: 25000 |
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download_size: 27928049 |
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dataset_size: 35294604 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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tags: |
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- math |
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- finance |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- text-generation |
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- question-answering |
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pretty_name: Simple Math |
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size_categories: |
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- 100K<n<1M |
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--- |
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|
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# Simple Math: 2+2=4 -1=3 (LoLo: Learning Only Logical Operations) |
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|
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Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models. |
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|
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It was created with very simple code that is in the repo, if you add more complex operations and so.. **please share the code** :D thank you |
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|
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Current Code Version: 20240127.fblgit (A modification over @win10 for progressive and DPO operation) |
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 |
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## Does it Works? |
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### 34BEAGLES Evaluation: |
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``` |
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hf (pretrained=/data/models/UNA-34Beagles-v1-final,dtype=bfloat16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto (8) |
|
| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr| |
|
|--------------|-------|------|-----:|--------|-----:|---|-----:| |
|
|arc_challenge |Yaml |none | 25|acc |0.7039|± |0.0133| |
|
| | |none | 25|acc_norm|0.7321|± |0.0129| |
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|truthfulqa_mc2|Yaml |none | 0|acc |0.7387|± |0.0141| |
|
|
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hf (pretrained=/data/models/UNA-34Beagles-v1-final,dtype=bfloat16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto |
|
|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr| |
|
|-----|-------|----------|-----:|-----------|-----:|---|-----:| |
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|gsm8k|Yaml |get-answer| 5|exact_match|0.6399|± |0.0132| |
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|
|
| Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |
|
|------------------|-------|------|-----:|------|-----:|---|-----:| |
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|mmlu |N/A |none | 0|acc |0.7477|± |0.1079| |
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| - humanities |N/A |none | 0|acc |0.7188|± |0.0855| |
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| - other |N/A |none | 0|acc |0.7950|± |0.1057| |
|
| - social_sciences|N/A |none | 0|acc |0.8297|± |0.0664| |
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| - stem |N/A |none | 0|acc |0.6641|± |0.1291| |
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``` |
|
|
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### 34BEAGLES-MATH Evaluation |
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``` |
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hf (pretrained=/data/models/34BeaglesMath-v1,dtype=bfloat16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto |
|
|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr| |
|
|-----|-------|----------|-----:|-----------|-----:|---|-----:| |
|
|gsm8k|Yaml |get-answer| 5|exact_match|0.6505|± |0.0131| |
|
|
|
hf (pretrained=/data/models/34BeaglesMath-v1,dtype=bfloat16,trust_remote_code=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: auto (8) |
|
| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr| |
|
|--------------|-------|------|-----:|--------|-----:|---|-----:| |
|
|arc_challenge |Yaml |none | 25|acc |0.7090|± |0.0133| |
|
| | |none | 25|acc_norm|0.7329|± |0.0129| |
|
|truthfulqa_mc2|Yaml |none | 0|acc |0.7378|± |0.0141| |
|
|
|
| Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |
|
|------------------|-------|------|-----:|------|-----:|---|-----:| |
|
|mmlu |N/A |none | 0|acc |0.7524|± |0.1045| |
|
| - humanities |N/A |none | 0|acc |0.7307|± |0.0846| |
|
| - other |N/A |none | 0|acc |0.7937|± |0.1029| |
|
| - social_sciences|N/A |none | 0|acc |0.8274|± |0.0667| |
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| - stem |N/A |none | 0|acc |0.6708|± |0.1236| |
|
``` |
|
|
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But it gets better, because when increasing length and complexity, the marks are even superior: |
|
``` |
|
|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr| |
|
|-----|-------|----------|-----:|-----------|-----:|---|-----:| |
|
|gsm8k|Yaml |get-answer| 5|exact_match|0.6611|± | 0.013| |
|
``` |
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On a 3.20% GSM Improvement compared to its base model. |
|
|
|
## Note to contributors: |
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**thank you to those contributing on the experiment with beautiful commits and good spirit** |
|
|
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* Feel free to contribute on the readme Evaluation tests. |
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* Lets aim to build an ablation & paper together. All contributors will be cited. |
|
|
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## Versions |
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``` |
|
27.01.24 Added new code to generate the dataset, seed 42 and now also generates DPO. |
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24.01.24 Added gradual complexity on a separate script |
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20-23.01.24 Multiple contributions with operations and increased complexity on the main generator script. |
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``` |
|
|
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## Citations |
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If you use Simple Math o train your model, please cite on the modelcard or the paper. |
|
|
|
``` |
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@misc{simplemath, |
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title={Simple-Math: 2+2=4 4-1=3}, |
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author={Xavier Murias}, |
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year={2024}, |
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publisher = {Juanako.AI}, |
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journal = {HuggingFace repository}, |
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howpublished = {\url{https://huggingface.co/datasets/fblgit/simple-math}}, |
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} |
|
``` |
