End of training
Browse files- README.md +13 -10
- model.safetensors +1 -1
README.md
CHANGED
@@ -11,7 +11,7 @@ datasets:
|
|
11 |
metrics:
|
12 |
- wer
|
13 |
model-index:
|
14 |
-
- name: Whisper
|
15 |
results:
|
16 |
- task:
|
17 |
name: Automatic Speech Recognition
|
@@ -22,18 +22,18 @@ model-index:
|
|
22 |
metrics:
|
23 |
- name: Wer
|
24 |
type: wer
|
25 |
-
value:
|
26 |
---
|
27 |
|
28 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
29 |
should probably proofread and complete it, then remove this comment. -->
|
30 |
|
31 |
-
# Whisper
|
32 |
|
33 |
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sunbird dataset.
|
34 |
It achieves the following results on the evaluation set:
|
35 |
-
- Loss: 2.
|
36 |
-
- Wer:
|
37 |
|
38 |
## Model description
|
39 |
|
@@ -52,26 +52,29 @@ More information needed
|
|
52 |
### Training hyperparameters
|
53 |
|
54 |
The following hyperparameters were used during training:
|
55 |
-
- learning_rate:
|
56 |
- train_batch_size: 16
|
57 |
- eval_batch_size: 8
|
58 |
- seed: 42
|
59 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
60 |
- lr_scheduler_type: linear
|
61 |
- lr_scheduler_warmup_steps: 1000
|
62 |
-
- training_steps:
|
63 |
- mixed_precision_training: Native AMP
|
64 |
|
65 |
### Training results
|
66 |
|
67 |
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
68 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
69 |
-
|
|
|
|
|
|
|
|
70 |
|
71 |
|
72 |
### Framework versions
|
73 |
|
74 |
- Transformers 4.38.0.dev0
|
75 |
- Pytorch 2.1.0+cu121
|
76 |
-
- Datasets 2.
|
77 |
-
- Tokenizers 0.15.
|
|
|
11 |
metrics:
|
12 |
- wer
|
13 |
model-index:
|
14 |
+
- name: Whisper base acholi
|
15 |
results:
|
16 |
- task:
|
17 |
name: Automatic Speech Recognition
|
|
|
22 |
metrics:
|
23 |
- name: Wer
|
24 |
type: wer
|
25 |
+
value: 122.26379794200186
|
26 |
---
|
27 |
|
28 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
29 |
should probably proofread and complete it, then remove this comment. -->
|
30 |
|
31 |
+
# Whisper base acholi
|
32 |
|
33 |
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sunbird dataset.
|
34 |
It achieves the following results on the evaluation set:
|
35 |
+
- Loss: 2.8895
|
36 |
+
- Wer: 122.2638
|
37 |
|
38 |
## Model description
|
39 |
|
|
|
52 |
### Training hyperparameters
|
53 |
|
54 |
The following hyperparameters were used during training:
|
55 |
+
- learning_rate: 1e-05
|
56 |
- train_batch_size: 16
|
57 |
- eval_batch_size: 8
|
58 |
- seed: 42
|
59 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
60 |
- lr_scheduler_type: linear
|
61 |
- lr_scheduler_warmup_steps: 1000
|
62 |
+
- training_steps: 4000
|
63 |
- mixed_precision_training: Native AMP
|
64 |
|
65 |
### Training results
|
66 |
|
67 |
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
68 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
69 |
+
| 3.2321 | 3.32 | 1000 | 2.9610 | 140.3181 |
|
70 |
+
| 2.5056 | 6.64 | 2000 | 2.7358 | 116.9317 |
|
71 |
+
| 2.0671 | 9.97 | 3000 | 2.7957 | 144.9953 |
|
72 |
+
| 1.7382 | 13.29 | 4000 | 2.8895 | 122.2638 |
|
73 |
|
74 |
|
75 |
### Framework versions
|
76 |
|
77 |
- Transformers 4.38.0.dev0
|
78 |
- Pytorch 2.1.0+cu121
|
79 |
+
- Datasets 2.17.1
|
80 |
+
- Tokenizers 0.15.2
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 290401888
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d539c48a948fa363ae9b87a8557cba4106e3f3b340fa505e6ec6ea5d9971808a
|
3 |
size 290401888
|