| --- |
| dataset_info: |
| features: |
| - name: output |
| dtype: string |
| - name: instruction |
| dtype: string |
| splits: |
| - name: arithmetic.float2_train |
| 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 |
| download_size: 27928049 |
| dataset_size: 35294604 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| tags: |
| - math |
| - finance |
| license: cc-by-nc-nd-4.0 |
| task_categories: |
| - text-generation |
| - question-answering |
| pretty_name: Simple Math |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # Simple Math: 2+2=4 -1=3 (LoLo: Learning Only Logical Operations) |
|
|
| Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models. |
|
|
| 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 |
|
|
| Current Code Version: 20240127.fblgit (A modification over @win10 for progressive and DPO operation) |
|  |
| ## Does it Works? |
| ### 34BEAGLES Evaluation: |
| ``` |
| 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| |
| |truthfulqa_mc2|Yaml |none | 0|acc |0.7387|± |0.0141| |
| |
| 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| |
| |-----|-------|----------|-----:|-----------|-----:|---|-----:| |
| |gsm8k|Yaml |get-answer| 5|exact_match|0.6399|± |0.0132| |
| |
| | Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |
| |------------------|-------|------|-----:|------|-----:|---|-----:| |
| |mmlu |N/A |none | 0|acc |0.7477|± |0.1079| |
| | - humanities |N/A |none | 0|acc |0.7188|± |0.0855| |
| | - other |N/A |none | 0|acc |0.7950|± |0.1057| |
| | - social_sciences|N/A |none | 0|acc |0.8297|± |0.0664| |
| | - stem |N/A |none | 0|acc |0.6641|± |0.1291| |
| ``` |
|
|
| ### 34BEAGLES-MATH Evaluation |
| ``` |
| 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| |
| | - stem |N/A |none | 0|acc |0.6708|± |0.1236| |
| ``` |
|
|
| 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| |
| ``` |
| On a 3.20% GSM Improvement compared to its base model. |
|
|
| ## Note to contributors: |
| **thank you to those contributing on the experiment with beautiful commits and good spirit** |
|
|
| * Feel free to contribute on the readme Evaluation tests. |
| * Lets aim to build an ablation & paper together. All contributors will be cited. |
|
|
| ## Versions |
| ``` |
| 27.01.24 Added new code to generate the dataset, seed 42 and now also generates DPO. |
| 24.01.24 Added gradual complexity on a separate script |
| 20-23.01.24 Multiple contributions with operations and increased complexity on the main generator script. |
| ``` |
|
|
| ## Citations |
| If you use Simple Math o train your model, please cite on the modelcard or the paper. |
|
|
| ``` |
| @misc{simplemath, |
| title={Simple-Math: 2+2=4 4-1=3}, |
| author={Xavier Murias}, |
| year={2024}, |
| publisher = {Juanako.AI}, |
| journal = {HuggingFace repository}, |
| howpublished = {\url{https://huggingface.co/datasets/fblgit/simple-math}}, |
| } |
| ``` |
