Update README.md
Browse files
README.md
CHANGED
@@ -16,6 +16,7 @@ datasets:
|
|
16 |
metrics:
|
17 |
- bleu
|
18 |
- wer
|
|
|
19 |
model-index:
|
20 |
- name: Whisper Small GA-EN Speech Translation
|
21 |
results:
|
@@ -23,7 +24,9 @@ model-index:
|
|
23 |
name: Automatic Speech Recognition
|
24 |
type: automatic-speech-recognition
|
25 |
dataset:
|
26 |
-
name:
|
|
|
|
|
27 |
type: ymoslem/IWSLT2023-GA-EN
|
28 |
metrics:
|
29 |
- name: Bleu
|
@@ -69,8 +72,10 @@ The following hyperparameters were used during training:
|
|
69 |
- seed: 42
|
70 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
71 |
- lr_scheduler_type: linear
|
|
|
72 |
- training_steps: 3000
|
73 |
- mixed_precision_training: Native AMP
|
|
|
74 |
|
75 |
### Training results
|
76 |
|
@@ -96,7 +101,7 @@ The following hyperparameters were used during training:
|
|
96 |
| 0.1946 | 0.7881 | 1800 | 1.2820 | 26.17 | 42.46 | 64.9257 |
|
97 |
| 0.1588 | 0.8319 | 1900 | 1.3172 | 26.9 | 43.02 | 63.5299 |
|
98 |
| 0.1322 | 0.8757 | 2000 | 1.3248 | 27.78 | 43.53 | 63.8001 |
|
99 |
-
| 0.1134 | 0.9194 | 2100 | 1.3198 | 28.98 | 45.27 | 72.7600 |
|
100 |
| 0.1031 | 0.9632 | 2200 | 1.3502 | 29.18 | 44.77 | 68.3476 |
|
101 |
| 0.0518 | 1.0070 | 2300 | 1.3433 | 28.6 | 42.96 | 69.0230 |
|
102 |
| 0.0481 | 1.0508 | 2400 | 1.3715 | 29.01 | 44.46 | 69.6983 |
|
@@ -113,4 +118,4 @@ The following hyperparameters were used during training:
|
|
113 |
- Transformers 4.40.2
|
114 |
- Pytorch 2.2.0+cu121
|
115 |
- Datasets 2.19.1
|
116 |
-
- Tokenizers 0.19.1
|
|
|
16 |
metrics:
|
17 |
- bleu
|
18 |
- wer
|
19 |
+
- chrf
|
20 |
model-index:
|
21 |
- name: Whisper Small GA-EN Speech Translation
|
22 |
results:
|
|
|
24 |
name: Automatic Speech Recognition
|
25 |
type: automatic-speech-recognition
|
26 |
dataset:
|
27 |
+
name: >-
|
28 |
+
IWSLT-2023, FLEURS, BiteSize, SpokenWords, Tatoeba, and Wikimedia +
|
29 |
+
augmented
|
30 |
type: ymoslem/IWSLT2023-GA-EN
|
31 |
metrics:
|
32 |
- name: Bleu
|
|
|
72 |
- seed: 42
|
73 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
74 |
- lr_scheduler_type: linear
|
75 |
+
- warmup_steps: 0
|
76 |
- training_steps: 3000
|
77 |
- mixed_precision_training: Native AMP
|
78 |
+
- generation_max_length: 128
|
79 |
|
80 |
### Training results
|
81 |
|
|
|
101 |
| 0.1946 | 0.7881 | 1800 | 1.2820 | 26.17 | 42.46 | 64.9257 |
|
102 |
| 0.1588 | 0.8319 | 1900 | 1.3172 | 26.9 | 43.02 | 63.5299 |
|
103 |
| 0.1322 | 0.8757 | 2000 | 1.3248 | 27.78 | 43.53 | 63.8001 |
|
104 |
+
| 0.1134 | 0.9194 | **2100** | 1.3198 | 28.98 | 45.27 | 72.7600 |
|
105 |
| 0.1031 | 0.9632 | 2200 | 1.3502 | 29.18 | 44.77 | 68.3476 |
|
106 |
| 0.0518 | 1.0070 | 2300 | 1.3433 | 28.6 | 42.96 | 69.0230 |
|
107 |
| 0.0481 | 1.0508 | 2400 | 1.3715 | 29.01 | 44.46 | 69.6983 |
|
|
|
118 |
- Transformers 4.40.2
|
119 |
- Pytorch 2.2.0+cu121
|
120 |
- Datasets 2.19.1
|
121 |
+
- Tokenizers 0.19.1
|