File size: 5,480 Bytes
18e4ca4 6d0e532 d13eb7a 117c4c1 6d0e532 d13eb7a 6d0e532 06065c2 18e4ca4 123376b 18e4ca4 06065c2 18e4ca4 adc5ed7 18e4ca4 123376b 18e4ca4 123376b 18e4ca4 123376b 06065c2 123376b 18e4ca4 6d0e532 |
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 |
---
license: apache-2.0
metrics:
- accuracy
inference:
parameters:
max_new_tokens: 64
do_sample: true
temperature: 0.7
repetition_penalty: 1.10
no_repeat_ngram_size: 6
eta_cutoff: 0.0008
renormalize_logits: true
widget:
- text: My name is El Microondas the Wise, and
example_title: El Microondas
- text: Kennesaw State University is a public
example_title: Kennesaw State University
- text: >-
Bungie Studios is an American video game developer. They are most famous for
developing the award winning Halo series of video games. They also made
Destiny. The studio was founded
example_title: Bungie
- text: The Mona Lisa is a world-renowned painting created by
example_title: Mona Lisa
- text: >-
The Harry Potter series, written by J.K. Rowling, begins with the book
titled
example_title: Harry Potter Series
- text: >-
Question: I have cities, but no houses. I have mountains, but no trees. I
have water, but no fish. What am I?
Answer:
example_title: Riddle
- text: The process of photosynthesis involves the conversion of
example_title: Photosynthesis
- text: >-
Jane went to the store to buy some groceries. She picked up apples, oranges,
and a loaf of bread. When she got home, she realized she forgot
example_title: Story Continuation
- text: >-
Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph, and
another train leaves Station B at 10:00 AM and travels at 80 mph, when will
they meet if the distance between the stations is 300 miles?
To determine
example_title: Math Problem
- text: In the context of computer programming, an algorithm is
example_title: Algorithm Definition
pipeline_tag: text-generation
datasets:
- BEE-spoke-data/UltraTextbooks-2.1-fw_mix
language:
- en
---
<!-- 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. -->
# mega-ar-350m-L3t-v0.08-ultraTBfw
## Model description
This is a pretraining experiment most recently trained on the BEE-spoke-data/UltraTextbooks-2.1-fw_mix dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0787
- Accuracy: 0.5746
- Num Input Tokens Seen: 3492282368
## Quick eval
Quick eval for: pszemraj/mega-ar-350m-L3t-v0.08-ultraTBfw
hf (pretrained=pszemraj/mega-ar-350m-L3t-v0.08-ultraTBfw,trust_remote_code=True,dtype=float), gen_kwargs: (None), limit: 0.99999, num_fewshot: None, batch_size: 8
| Tasks |Version|Filter|n-shot| Metric | Value | |Stderr|
|--------------|------:|------|-----:|----------|------:|---|-----:|
|arc_easy | 1|none | 0|acc | 0.4246|± |0.0139|
| | |none | 0|acc_norm | 0.4002|± |0.0138|
|boolq | 2|none | 0|acc | 0.5762|± |0.0139|
|lambada_openai| 1|none | 0|perplexity|76.7162|± |6.3531|
| | |none | 0|acc | 0.2605|± |0.0123|
|openbookqa | 1|none | 0|acc | 0.1840|± |0.0173|
| | |none | 0|acc_norm | 0.2720|± |0.0199|
|piqa | 1|none | 0|acc | 0.6377|± |0.0135|
| | |none | 0|acc_norm | 0.6172|± |0.0137|
|winogrande | 1|none | 0|acc | 0.5020|± |0.0141|
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 80085
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 2.2572 | 0.0600 | 400 | 2.2462 | 0.5491 | 209715200 |
| 2.2173 | 0.1201 | 800 | 2.1939 | 0.5564 | 419430400 |
| 2.1992 | 0.1801 | 1200 | 2.1689 | 0.5604 | 629145600 |
| 2.1543 | 0.2402 | 1600 | 2.1521 | 0.5632 | 838860800 |
| 2.1532 | 0.3002 | 2000 | 2.1401 | 0.5650 | 1048576000 |
| 2.1688 | 0.3603 | 2400 | 2.1307 | 0.5663 | 1258291200 |
| 2.1443 | 0.4203 | 2800 | 2.1227 | 0.5676 | 1468006400 |
| 2.1105 | 0.4804 | 3200 | 2.1158 | 0.5689 | 1677721600 |
| 2.1045 | 0.5404 | 3600 | 2.1090 | 0.5700 | 1887436800 |
| 2.1181 | 0.6004 | 4000 | 2.1045 | 0.5708 | 2097152000 |
| 2.127 | 0.6605 | 4400 | 2.0994 | 0.5716 | 2306867200 |
| 2.1265 | 0.7205 | 4800 | 2.0958 | 0.5719 | 2516582400 |
| 2.0951 | 0.7806 | 5200 | 2.0909 | 0.5728 | 2726297600 |
| 2.0951 | 0.8406 | 5600 | 2.0876 | 0.5733 | 2936012800 |
| 2.1335 | 0.9007 | 6000 | 2.0838 | 0.5739 | 3145728000 |
| 2.0731 | 0.9607 | 6400 | 2.0802 | 0.5744 | 3355443200 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |