End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,71 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- jpn
|
| 4 |
+
license: apache-2.0
|
| 5 |
+
base_model: openai/whisper-small
|
| 6 |
+
tags:
|
| 7 |
+
- speaker-diarization
|
| 8 |
+
- speaker-segmentation
|
| 9 |
+
- generated_from_trainer
|
| 10 |
+
datasets:
|
| 11 |
+
- diarizers-community/callhome
|
| 12 |
+
model-index:
|
| 13 |
+
- name: speaker-segmentation-fine-tuned-callhome-jpn
|
| 14 |
+
results: []
|
| 15 |
+
---
|
| 16 |
+
|
| 17 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 18 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 19 |
+
|
| 20 |
+
# speaker-segmentation-fine-tuned-callhome-jpn
|
| 21 |
+
|
| 22 |
+
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the diarizers-community/callhome dataset.
|
| 23 |
+
It achieves the following results on the evaluation set:
|
| 24 |
+
- Loss: 0.7490
|
| 25 |
+
- Der: 0.2217
|
| 26 |
+
- False Alarm: 0.0465
|
| 27 |
+
- Missed Detection: 0.1331
|
| 28 |
+
- Confusion: 0.0421
|
| 29 |
+
|
| 30 |
+
## Model description
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Intended uses & limitations
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training and evaluation data
|
| 39 |
+
|
| 40 |
+
More information needed
|
| 41 |
+
|
| 42 |
+
## Training procedure
|
| 43 |
+
|
| 44 |
+
### Training hyperparameters
|
| 45 |
+
|
| 46 |
+
The following hyperparameters were used during training:
|
| 47 |
+
- learning_rate: 0.001
|
| 48 |
+
- train_batch_size: 32
|
| 49 |
+
- eval_batch_size: 32
|
| 50 |
+
- seed: 42
|
| 51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 52 |
+
- lr_scheduler_type: cosine
|
| 53 |
+
- num_epochs: 5
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
|
| 59 |
+
| 0.575 | 1.0 | 328 | 0.7539 | 0.2338 | 0.0503 | 0.1345 | 0.0489 |
|
| 60 |
+
| 0.5261 | 2.0 | 656 | 0.7483 | 0.2256 | 0.0485 | 0.1334 | 0.0436 |
|
| 61 |
+
| 0.5048 | 3.0 | 984 | 0.7581 | 0.2248 | 0.0440 | 0.1373 | 0.0435 |
|
| 62 |
+
| 0.4911 | 4.0 | 1312 | 0.7467 | 0.2226 | 0.0472 | 0.1330 | 0.0424 |
|
| 63 |
+
| 0.5161 | 5.0 | 1640 | 0.7490 | 0.2217 | 0.0465 | 0.1331 | 0.0421 |
|
| 64 |
+
|
| 65 |
+
|
| 66 |
+
### Framework versions
|
| 67 |
+
|
| 68 |
+
- Transformers 4.40.2
|
| 69 |
+
- Pytorch 2.2.1+cu121
|
| 70 |
+
- Datasets 2.19.1
|
| 71 |
+
- Tokenizers 0.19.1
|
runs/May21_05-59-21_0e401c69515e/events.out.tfevents.1716271194.0e401c69515e.175.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:47ac52defae94f5e2796964c98f306021864118e54f5fbb078e325ceb303f18a
|
| 3 |
+
size 21280
|