File size: 3,669 Bytes
b44d47d 752efd1 b44d47d d41b375 752efd1 d41b375 752efd1 b44d47d d41b375 b44d47d 752efd1 b44d47d 752efd1 b44d47d 752efd1 b44d47d 752efd1 b44d47d 752efd1 b44d47d 752efd1 |
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 |
---
license: apache-2.0
base_model: pszemraj/tinyllama-1.1b-3T
tags:
- bees
- bzz
- honey
- oprah winfrey
metrics:
- accuracy
inference:
parameters:
max_new_tokens: 64
do_sample: true
renormalize_logits: true
repetition_penalty: 1.05
no_repeat_ngram_size: 6
temperature: 0.9
top_p: 0.95
epsilon_cutoff: 0.0008
widget:
- text: In beekeeping, the term "queen excluder" refers to
example_title: Queen Excluder
- text: One way to encourage a honey bee colony to produce more honey is by
example_title: Increasing Honey Production
- text: The lifecycle of a worker bee consists of several stages, starting with
example_title: Lifecycle of a Worker Bee
- text: Varroa destructor is a type of mite that
example_title: Varroa Destructor
- text: In the world of beekeeping, the acronym PPE stands for
example_title: Beekeeping PPE
- text: The term "robbing" in beekeeping refers to the act of
example_title: Robbing in Beekeeping
- text: |-
Question: What's the primary function of drone bees in a hive?
Answer:
example_title: Role of Drone Bees
- text: To harvest honey from a hive, beekeepers often use a device known as a
example_title: Honey Harvesting Device
- text: >-
Problem: You have a hive that produces 60 pounds of honey per year. You
decide to split the hive into two. Assuming each hive now produces at a 70%
rate compared to before, how much honey will you get from both hives next
year?
To calculate
example_title: Beekeeping Math Problem
- text: In beekeeping, "swarming" is the process where
example_title: Swarming
pipeline_tag: text-generation
datasets:
- BEE-spoke-data/bees-internal
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. -->
# TinyLlama-3T-1.1bee
A grand successor to [the original](https://huggingface.co/BEE-spoke-data/TinyLlama-1.1bee). This one has the following improvements:
- start from [finished 3T TinyLlama](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T)
- vastly improved and expanded SoTA beekeeping dataset
## Model description
This model is a fine-tuned version of TinyLlama-1.1b-3T on the BEE-spoke-data/bees-internal dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1640
- Accuracy: 0.5406
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 13707
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4432 | 0.19 | 50 | 2.3850 | 0.5033 |
| 2.3655 | 0.39 | 100 | 2.3124 | 0.5129 |
| 2.374 | 0.58 | 150 | 2.2588 | 0.5215 |
| 2.3558 | 0.78 | 200 | 2.2132 | 0.5291 |
| 2.2677 | 0.97 | 250 | 2.1828 | 0.5348 |
| 2.0701 | 1.17 | 300 | 2.1788 | 0.5373 |
| 2.0766 | 1.36 | 350 | 2.1673 | 0.5398 |
| 2.0669 | 1.56 | 400 | 2.1651 | 0.5402 |
| 2.0314 | 1.75 | 450 | 2.1641 | 0.5406 |
| 2.0281 | 1.95 | 500 | 2.1639 | 0.5407 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0
- Datasets 2.16.1
- Tokenizers 0.15.0 |