Hugging Face's logo

susmitabhatt
/
superb-wav2vec2

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
susmitabhatt commited on
Commit
ee1fbab
·
verified ·
1 Parent(s): 2d20e10

End of training

Browse files
Files changed (3) hide show
  1. README.md +132 -195
  2. model.safetensors +1 -1
  3. runs/Sep10_11-31-36_f1ddc92f9190/events.out.tfevents.1725967933.f1ddc92f9190.37.0 +2 -2
README.md CHANGED
@@ -1,199 +1,136 @@
1
  ---
2
  library_name: transformers
3
- tags: []
 
 
 
 
 
 
 
4
  ---
5
 
6
- # Model Card for Model ID
7
-
8
- <!-- Provide a quick summary of what the model is/does. -->
9
-
10
-
11
-
12
- ## Model Details
13
-
14
- ### Model Description
15
-
16
- <!-- Provide a longer summary of what this model is. -->
17
-
18
- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
-
20
- - **Developed by:** [More Information Needed]
21
- - **Funded by [optional]:** [More Information Needed]
22
- - **Shared by [optional]:** [More Information Needed]
23
- - **Model type:** [More Information Needed]
24
- - **Language(s) (NLP):** [More Information Needed]
25
- - **License:** [More Information Needed]
26
- - **Finetuned from model [optional]:** [More Information Needed]
27
-
28
- ### Model Sources [optional]
29
-
30
- <!-- Provide the basic links for the model. -->
31
-
32
- - **Repository:** [More Information Needed]
33
- - **Paper [optional]:** [More Information Needed]
34
- - **Demo [optional]:** [More Information Needed]
35
-
36
- ## Uses
37
-
38
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
-
40
- ### Direct Use
41
-
42
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
-
44
- [More Information Needed]
45
-
46
- ### Downstream Use [optional]
47
-
48
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
-
50
- [More Information Needed]
51
-
52
- ### Out-of-Scope Use
53
-
54
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
-
56
- [More Information Needed]
57
-
58
- ## Bias, Risks, and Limitations
59
-
60
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
-
62
- [More Information Needed]
63
-
64
- ### Recommendations
65
-
66
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
-
68
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
-
70
- ## How to Get Started with the Model
71
-
72
- Use the code below to get started with the model.
73
-
74
- [More Information Needed]
75
-
76
- ## Training Details
77
-
78
- ### Training Data
79
-
80
- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
-
82
- [More Information Needed]
83
-
84
- ### Training Procedure
85
-
86
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
-
88
- #### Preprocessing [optional]
89
-
90
- [More Information Needed]
91
-
92
-
93
- #### Training Hyperparameters
94
-
95
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
-
97
- #### Speeds, Sizes, Times [optional]
98
-
99
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
-
101
- [More Information Needed]
102
-
103
- ## Evaluation
104
-
105
- <!-- This section describes the evaluation protocols and provides the results. -->
106
-
107
- ### Testing Data, Factors & Metrics
108
-
109
- #### Testing Data
110
-
111
- <!-- This should link to a Dataset Card if possible. -->
112
-
113
- [More Information Needed]
114
-
115
- #### Factors
116
-
117
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
-
119
- [More Information Needed]
120
-
121
- #### Metrics
122
-
123
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
-
125
- [More Information Needed]
126
-
127
- ### Results
128
-
129
- [More Information Needed]
130
-
131
- #### Summary
132
-
133
-
134
-
135
- ## Model Examination [optional]
136
-
137
- <!-- Relevant interpretability work for the model goes here -->
138
-
139
- [More Information Needed]
140
-
141
- ## Environmental Impact
142
-
143
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
-
145
- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
-
147
- - **Hardware Type:** [More Information Needed]
148
- - **Hours used:** [More Information Needed]
149
- - **Cloud Provider:** [More Information Needed]
150
- - **Compute Region:** [More Information Needed]
151
- - **Carbon Emitted:** [More Information Needed]
152
-
153
- ## Technical Specifications [optional]
154
-
155
- ### Model Architecture and Objective
156
-
157
- [More Information Needed]
158
-
159
- ### Compute Infrastructure
160
-
161
- [More Information Needed]
162
-
163
- #### Hardware
164
-
165
- [More Information Needed]
166
-
167
- #### Software
168
-
169
- [More Information Needed]
170
-
171
- ## Citation [optional]
172
-
173
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
-
175
- **BibTeX:**
176
-
177
- [More Information Needed]
178
-
179
- **APA:**
180
-
181
- [More Information Needed]
182
-
183
- ## Glossary [optional]
184
-
185
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
-
187
- [More Information Needed]
188
-
189
- ## More Information [optional]
190
-
191
- [More Information Needed]
192
-
193
- ## Model Card Authors [optional]
194
-
195
- [More Information Needed]
196
-
197
- ## Model Card Contact
198
-
199
- [More Information Needed]
 
1
  ---
2
  library_name: transformers
3
+ base_model: vasista22/ccc-wav2vec2-base-SUPERB
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - wer
8
+ model-index:
9
+ - name: superb-wav2vec2
10
+ results: []
11
  ---
12
 
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # superb-wav2vec2
17
+
18
+ This model is a fine-tuned version of [vasista22/ccc-wav2vec2-base-SUPERB](https://huggingface.co/vasista22/ccc-wav2vec2-base-SUPERB) on the None dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.0003
21
+ - Wer: 0.0233
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 0.0004
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 8
43
+ - seed: 42
44
+ - gradient_accumulation_steps: 2
45
+ - total_train_batch_size: 16
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - lr_scheduler_warmup_steps: 132
49
+ - num_epochs: 30
50
+ - mixed_precision_training: Native AMP
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Wer |
55
+ |:-------------:|:-------:|:----:|:---------------:|:------:|
56
+ | 3.0211 | 0.4082 | 50 | 2.0267 | 0.9861 |
57
+ | 1.9496 | 0.8163 | 100 | 1.7685 | 0.9849 |
58
+ | 1.7178 | 1.2245 | 150 | 1.4738 | 0.8240 |
59
+ | 1.3801 | 1.6327 | 200 | 1.1281 | 0.8227 |
60
+ | 1.189 | 2.0408 | 250 | 0.8568 | 0.5723 |
61
+ | 0.9318 | 2.4490 | 300 | 0.6622 | 0.5615 |
62
+ | 0.7042 | 2.8571 | 350 | 0.3612 | 0.3023 |
63
+ | 0.5805 | 3.2653 | 400 | 0.4220 | 0.4606 |
64
+ | 0.4229 | 3.6735 | 450 | 0.1465 | 0.1417 |
65
+ | 0.3913 | 4.0816 | 500 | 0.1350 | 0.1688 |
66
+ | 0.2645 | 4.4898 | 550 | 0.1030 | 0.1421 |
67
+ | 0.2809 | 4.8980 | 600 | 0.0867 | 0.0977 |
68
+ | 0.2344 | 5.3061 | 650 | 0.0901 | 0.1367 |
69
+ | 0.1703 | 5.7143 | 700 | 0.0659 | 0.1246 |
70
+ | 0.1718 | 6.1224 | 750 | 0.0432 | 0.0545 |
71
+ | 0.1442 | 6.5306 | 800 | 0.0636 | 0.0824 |
72
+ | 0.1494 | 6.9388 | 850 | 0.0431 | 0.0448 |
73
+ | 0.1492 | 7.3469 | 900 | 0.0328 | 0.0478 |
74
+ | 0.1185 | 7.7551 | 950 | 0.0376 | 0.0621 |
75
+ | 0.107 | 8.1633 | 1000 | 0.0249 | 0.0241 |
76
+ | 0.1159 | 8.5714 | 1050 | 0.0350 | 0.0396 |
77
+ | 0.1015 | 8.9796 | 1100 | 0.0232 | 0.0334 |
78
+ | 0.1203 | 9.3878 | 1150 | 0.0341 | 0.0780 |
79
+ | 0.0835 | 9.7959 | 1200 | 0.0178 | 0.0458 |
80
+ | 0.1239 | 10.2041 | 1250 | 0.0231 | 0.0543 |
81
+ | 0.0859 | 10.6122 | 1300 | 0.0163 | 0.0289 |
82
+ | 0.0732 | 11.0204 | 1350 | 0.0309 | 0.0494 |
83
+ | 0.063 | 11.4286 | 1400 | 0.0168 | 0.0963 |
84
+ | 0.0693 | 11.8367 | 1450 | 0.0268 | 0.0619 |
85
+ | 0.0649 | 12.2449 | 1500 | 0.0328 | 0.0687 |
86
+ | 0.063 | 12.6531 | 1550 | 0.0173 | 0.0438 |
87
+ | 0.0574 | 13.0612 | 1600 | 0.0118 | 0.0506 |
88
+ | 0.0438 | 13.4694 | 1650 | 0.0101 | 0.0510 |
89
+ | 0.0556 | 13.8776 | 1700 | 0.0064 | 0.0291 |
90
+ | 0.0536 | 14.2857 | 1750 | 0.0098 | 0.0225 |
91
+ | 0.047 | 14.6939 | 1800 | 0.0157 | 0.0251 |
92
+ | 0.0588 | 15.1020 | 1850 | 0.0097 | 0.0291 |
93
+ | 0.0397 | 15.5102 | 1900 | 0.0113 | 0.0541 |
94
+ | 0.0375 | 15.9184 | 1950 | 0.0173 | 0.0531 |
95
+ | 0.0411 | 16.3265 | 2000 | 0.0079 | 0.0394 |
96
+ | 0.0382 | 16.7347 | 2050 | 0.0056 | 0.0340 |
97
+ | 0.0448 | 17.1429 | 2100 | 0.0064 | 0.0287 |
98
+ | 0.0359 | 17.5510 | 2150 | 0.0053 | 0.0261 |
99
+ | 0.032 | 17.9592 | 2200 | 0.0091 | 0.0400 |
100
+ | 0.0295 | 18.3673 | 2250 | 0.0018 | 0.0275 |
101
+ | 0.03 | 18.7755 | 2300 | 0.0034 | 0.0259 |
102
+ | 0.0246 | 19.1837 | 2350 | 0.0280 | 0.0368 |
103
+ | 0.0465 | 19.5918 | 2400 | 0.0099 | 0.0297 |
104
+ | 0.0264 | 20.0 | 2450 | 0.0063 | 0.0111 |
105
+ | 0.025 | 20.4082 | 2500 | 0.0015 | 0.0370 |
106
+ | 0.04 | 20.8163 | 2550 | 0.0020 | 0.0344 |
107
+ | 0.0203 | 21.2245 | 2600 | 0.0055 | 0.0356 |
108
+ | 0.0241 | 21.6327 | 2650 | 0.0024 | 0.0299 |
109
+ | 0.0465 | 22.0408 | 2700 | 0.0022 | 0.0392 |
110
+ | 0.0283 | 22.4490 | 2750 | 0.0026 | 0.0149 |
111
+ | 0.0134 | 22.8571 | 2800 | 0.0015 | 0.0177 |
112
+ | 0.0177 | 23.2653 | 2850 | 0.0041 | 0.0177 |
113
+ | 0.0288 | 23.6735 | 2900 | 0.0011 | 0.0147 |
114
+ | 0.0216 | 24.0816 | 2950 | 0.0034 | 0.0287 |
115
+ | 0.0147 | 24.4898 | 3000 | 0.0046 | 0.0155 |
116
+ | 0.0118 | 24.8980 | 3050 | 0.0021 | 0.0235 |
117
+ | 0.0113 | 25.3061 | 3100 | 0.0012 | 0.0261 |
118
+ | 0.0135 | 25.7143 | 3150 | 0.0006 | 0.0261 |
119
+ | 0.0118 | 26.1224 | 3200 | 0.0008 | 0.0287 |
120
+ | 0.0083 | 26.5306 | 3250 | 0.0004 | 0.0257 |
121
+ | 0.0148 | 26.9388 | 3300 | 0.0006 | 0.0261 |
122
+ | 0.0081 | 27.3469 | 3350 | 0.0005 | 0.0263 |
123
+ | 0.0192 | 27.7551 | 3400 | 0.0004 | 0.0237 |
124
+ | 0.0096 | 28.1633 | 3450 | 0.0004 | 0.0231 |
125
+ | 0.0083 | 28.5714 | 3500 | 0.0003 | 0.0215 |
126
+ | 0.0056 | 28.9796 | 3550 | 0.0004 | 0.0233 |
127
+ | 0.0082 | 29.3878 | 3600 | 0.0003 | 0.0233 |
128
+ | 0.0102 | 29.7959 | 3650 | 0.0003 | 0.0233 |
129
+
130
+
131
+ ### Framework versions
132
+
133
+ - Transformers 4.45.0.dev0
134
+ - Pytorch 2.4.0
135
+ - Datasets 2.21.0
136
+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3a31e76e22f574a2aabb28d3adac0e1ff378cbb1c2a533b0e3fe40646ed4fa7e
3
  size 377601892
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a715b49bdbf050cc6ddcf5e8443f27fb77fb13726c88f58c03610ced6c926758
3
  size 377601892
runs/Sep10_11-31-36_f1ddc92f9190/events.out.tfevents.1725967933.f1ddc92f9190.37.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5a4a19337026af2f5ddd2e53ea9db8ea8d39579879ed9fb02b92c50f2ce4e308
3
- size 45282
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9b81c3e83c890d4e8d5fd2ec30f505c17e5c72d6b7f5548615226cf38dd44413
3
+ size 45636