File size: 2,893 Bytes
da28d5c b93ed14 f4aa9cf 63dc90b da28d5c 63dc90b f4aa9cf 63dc90b f4aa9cf 63dc90b f4aa9cf 63dc90b |
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 |
---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: classify-ISIN-STEP6_binary
results: []
---
<!-- 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. -->
# classify-ISIN-STEP6_binary
This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
- Accuracy Label Gd622:null: 1.0
- Accuracy Label Gd622:yes: 1.0
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Gd622:null | Accuracy Label Gd622:yes |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|:-------------------------:|:------------------------:|
| 0.0056 | 2.4691 | 100 | 0.0042 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.001 | 4.9383 | 200 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0005 | 7.4074 | 300 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0003 | 9.8765 | 400 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 12.3457 | 500 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 14.8148 | 600 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 17.2840 | 700 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 19.7531 | 800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|