lighteternal commited on
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626bc84
1 Parent(s): 75ed774

Added new model weights and info, trained on CV and CSS

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  1. .ipynb_checkpoints/ASR_Inference-checkpoint.ipynb +498 -135
  2. ASR_Inference.ipynb +498 -135
  3. README.md +8 -6
  4. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429242.mp3 +0 -0
  5. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429243.mp3 +0 -0
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  34. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429328.mp3 +0 -0
  35. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429329.mp3 +0 -0
  36. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429330.mp3 +0 -0
  37. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429331.mp3 +0 -0
  38. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429332.mp3 +0 -0
  39. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429407.mp3 +0 -0
  40. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429408.mp3 +0 -0
  41. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429410.mp3 +0 -0
  42. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429411.mp3 +0 -0
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  44. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429418.mp3 +0 -0
  45. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429419.mp3 +0 -0
  46. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429420.mp3 +0 -0
  47. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429421.mp3 +0 -0
  48. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429422.mp3 +0 -0
  49. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429438.mp3 +0 -0
  50. cv-corpus-6.1-2020-12-11/el/clips/common_voice_el_20429439.mp3 +0 -0
.ipynb_checkpoints/ASR_Inference-checkpoint.ipynb CHANGED
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  "# πού θέλεις να πάμε; ρώτησε φοβισμένα ο βασιλιάς."
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+ "name": "stdout",
748
+ "output_type": "stream",
749
+ "text": [
750
+ "\r",
751
+ "Dataset common_voice downloaded and prepared to /home/earendil/.cache/huggingface/datasets/common_voice/el-ac779bf2c9f7c09b/6.1.0/0041e06ab061b91d0a23234a2221e87970a19cf3a81b20901474cffffeb7869f. Subsequent calls will reuse this data.\n"
752
  ]
753
  }
754
  ],
 
809
  "# πού θέλεις να πάμε; ρώτησε φοβισμένα ο βασιλιάς."
810
  ]
811
  },
812
+ {
813
+ "cell_type": "code",
814
+ "execution_count": 13,
815
+ "metadata": {
816
+ "ExecuteTime": {
817
+ "end_time": "2021-03-17T11:15:35.637739Z",
818
+ "start_time": "2021-03-17T11:14:14.689842Z"
819
+ }
820
+ },
821
+ "outputs": [
822
+ {
823
+ "data": {
824
+ "application/vnd.jupyter.widget-view+json": {
825
+ "model_id": "1f7ba9e12187401f870555d20a6a9458",
826
+ "version_major": 2,
827
+ "version_minor": 0
828
+ },
829
+ "text/plain": [
830
+ "HBox(children=(IntProgress(value=0, max=1522), HTML(value='')))"
831
+ ]
832
+ },
833
+ "metadata": {},
834
+ "output_type": "display_data"
835
+ },
836
+ {
837
+ "name": "stdout",
838
+ "output_type": "stream",
839
+ "text": [
840
+ "\n"
841
+ ]
842
+ }
843
+ ],
844
+ "source": [
845
+ "def map_to_result(batch):\n",
846
+ " model.to(\"cuda\")\n",
847
+ " input_values = processor(\n",
848
+ " batch[\"input_values\"], \n",
849
+ " sampling_rate=16_000, \n",
850
+ " return_tensors=\"pt\"\n",
851
+ " ).input_values.to(\"cuda\")\n",
852
+ "\n",
853
+ " with torch.no_grad():\n",
854
+ " logits = model(input_values).logits\n",
855
+ "\n",
856
+ " pred_ids = torch.argmax(logits, dim=-1)\n",
857
+ " batch[\"pred_str\"] = processor.batch_decode(pred_ids)[0]\n",
858
+ "\n",
859
+ " return batch\n",
860
+ "\n",
861
+ "results = common_voice_test.map(map_to_result)\n"
862
+ ]
863
+ },
864
+ {
865
+ "cell_type": "code",
866
+ "execution_count": 16,
867
+ "metadata": {
868
+ "ExecuteTime": {
869
+ "end_time": "2021-03-17T11:17:11.951524Z",
870
+ "start_time": "2021-03-17T11:17:08.856552Z"
871
+ }
872
+ },
873
+ "outputs": [
874
+ {
875
+ "name": "stdout",
876
+ "output_type": "stream",
877
+ "text": [
878
+ "Test WER: 0.396\n"
879
+ ]
880
+ }
881
+ ],
882
+ "source": [
883
+ "def compute_metrics(pred):\n",
884
+ " pred_logits = pred.predictions\n",
885
+ " pred_ids = np.argmax(pred_logits, axis=-1)\n",
886
+ "\n",
887
+ " pred.label_ids[pred.label_ids == -100] = processor.tokenizer.pad_token_id\n",
888
+ "\n",
889
+ " pred_str = processor.batch_decode(pred_ids)\n",
890
+ " # we do not want to group tokens when computing the metrics\n",
891
+ " label_str = processor.batch_decode(pred.label_ids, group_tokens=False)\n",
892
+ "\n",
893
+ " wer = wer_metric.compute(predictions=pred_str, references=label_str)\n",
894
+ "\n",
895
+ " return {\"wer\": wer}\n",
896
+ "\n",
897
+ "wer_metric = load_metric(\"wer\")\n",
898
+ "\n",
899
+ "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results[\"pred_str\"], references= [item.lower() for item in common_voice_test_transcription['sentence']])))"
900
+ ]
901
+ },
902
  {
903
  "cell_type": "code",
904
  "execution_count": null,
ASR_Inference.ipynb CHANGED
@@ -5,8 +5,8 @@
5
  "execution_count": 1,
6
  "metadata": {
7
  "ExecuteTime": {
8
- "end_time": "2021-03-14T19:32:40.765119Z",
9
- "start_time": "2021-03-14T19:32:39.314790Z"
10
  }
11
  },
12
  "outputs": [
@@ -36,8 +36,8 @@
36
  "execution_count": 2,
37
  "metadata": {
38
  "ExecuteTime": {
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- "end_time": "2021-03-14T19:32:40.774860Z",
40
- "start_time": "2021-03-14T19:32:40.771235Z"
41
  }
42
  },
43
  "outputs": [],
@@ -75,11 +75,11 @@
75
  },
76
  {
77
  "cell_type": "code",
78
- "execution_count": 3,
79
  "metadata": {
80
  "ExecuteTime": {
81
- "end_time": "2021-03-14T19:32:49.565850Z",
82
- "start_time": "2021-03-14T19:32:41.891601Z"
83
  }
84
  },
85
  "outputs": [
@@ -98,11 +98,11 @@
98
  },
99
  {
100
  "cell_type": "code",
101
- "execution_count": 4,
102
  "metadata": {
103
  "ExecuteTime": {
104
- "end_time": "2021-03-14T19:33:03.514113Z",
105
- "start_time": "2021-03-14T19:33:00.953049Z"
106
  }
107
  },
108
  "outputs": [
@@ -110,8 +110,120 @@
110
  "name": "stderr",
111
  "output_type": "stream",
112
  "text": [
113
- "Using custom data configuration el-afd0a157f05ee080\n",
114
- "Reusing dataset common_voice (/home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564)\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
115
  ]
116
  }
117
  ],
@@ -121,11 +233,11 @@
121
  },
122
  {
123
  "cell_type": "code",
124
- "execution_count": 5,
125
  "metadata": {
126
  "ExecuteTime": {
127
- "end_time": "2021-03-14T19:33:03.528699Z",
128
- "start_time": "2021-03-14T19:33:03.525034Z"
129
  }
130
  },
131
  "outputs": [],
@@ -135,19 +247,33 @@
135
  },
136
  {
137
  "cell_type": "code",
138
- "execution_count": 6,
139
  "metadata": {
140
  "ExecuteTime": {
141
- "end_time": "2021-03-14T19:33:03.542260Z",
142
- "start_time": "2021-03-14T19:33:03.538498Z"
143
  }
144
  },
145
  "outputs": [
146
  {
147
- "name": "stderr",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
148
  "output_type": "stream",
149
  "text": [
150
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-0ce2ebca66096fff.arrow\n"
151
  ]
152
  }
153
  ],
@@ -157,19 +283,33 @@
157
  },
158
  {
159
  "cell_type": "code",
160
- "execution_count": 7,
161
  "metadata": {
162
  "ExecuteTime": {
163
- "end_time": "2021-03-14T19:33:03.561798Z",
164
- "start_time": "2021-03-14T19:33:03.554256Z"
165
  }
166
  },
167
  "outputs": [
168
  {
169
- "name": "stderr",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
170
  "output_type": "stream",
171
  "text": [
172
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-38a09981767eff59.arrow\n"
173
  ]
174
  }
175
  ],
@@ -179,11 +319,11 @@
179
  },
180
  {
181
  "cell_type": "code",
182
- "execution_count": 8,
183
  "metadata": {
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186
- "start_time": "2021-03-14T19:33:03.570805Z"
187
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188
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189
  "outputs": [
@@ -191,112 +331,133 @@
191
  "name": "stdout",
192
  "output_type": "stream",
193
  "text": [
194
- " "
195
- ]
196
- },
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- {
198
- "name": "stderr",
199
- "output_type": "stream",
200
- "text": [
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- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-ba8c6dd59eb8ccf2.arrow\n"
202
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206
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209
- ]
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- },
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- {
212
- "name": "stderr",
213
- "output_type": "stream",
214
- "text": [
215
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-2e240883a5f827fd.arrow\n"
216
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217
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218
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220
- "output_type": "stream",
221
- "text": [
222
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223
- ]
224
- },
225
- {
226
- "name": "stderr",
227
- "output_type": "stream",
228
- "text": [
229
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-485c00dc9048ed50.arrow\n"
230
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231
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232
  {
233
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234
- "output_type": "stream",
235
- "text": [
236
- " "
237
- ]
 
 
 
 
 
 
 
238
  },
239
  {
240
- "name": "stderr",
241
- "output_type": "stream",
242
- "text": [
243
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-44bf1791baae8e2e.arrow\n"
244
- ]
 
 
 
 
 
 
 
245
  },
246
  {
247
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248
- "output_type": "stream",
249
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250
- " "
251
- ]
 
 
 
 
 
 
 
252
  },
253
  {
254
- "name": "stderr",
255
- "output_type": "stream",
256
- "text": [
257
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-ecc0dfac5615a58e.arrow\n"
258
- ]
 
 
 
 
 
 
 
259
  },
260
  {
261
- "name": "stdout",
262
- "output_type": "stream",
263
- "text": [
264
- " "
265
- ]
 
 
 
 
 
 
 
266
  },
267
  {
268
- "name": "stderr",
269
- "output_type": "stream",
270
- "text": [
271
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-923d905502a8661d.arrow\n"
272
- ]
 
 
 
 
 
 
 
273
  },
274
  {
275
- "name": "stdout",
276
- "output_type": "stream",
277
- "text": [
278
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279
- ]
 
 
 
 
 
 
 
280
  },
281
  {
282
- "name": "stderr",
283
- "output_type": "stream",
284
- "text": [
285
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-bb54bb00dae79669.arrow\n"
286
- ]
 
 
 
 
 
 
 
287
  },
288
  {
289
  "name": "stdout",
290
  "output_type": "stream",
291
  "text": [
292
- " "
293
- ]
294
- },
295
- {
296
- "name": "stderr",
297
- "output_type": "stream",
298
- "text": [
299
- "Loading cached processed dataset at /home/earendil/.cache/huggingface/datasets/common_voice/el-afd0a157f05ee080/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564/cache-062aeafc3b8816c1.arrow\n"
300
  ]
301
  }
302
  ],
@@ -306,11 +467,11 @@
306
  },
307
  {
308
  "cell_type": "code",
309
- "execution_count": 9,
310
  "metadata": {
311
  "ExecuteTime": {
312
- "end_time": "2021-03-14T19:33:11.205598Z",
313
- "start_time": "2021-03-14T19:33:04.368615Z"
314
  }
315
  },
316
  "outputs": [
@@ -332,12 +493,12 @@
332
  {
333
  "data": {
334
  "application/vnd.jupyter.widget-view+json": {
335
- "model_id": "b179696d93284b739cc550511ca28b78",
336
  "version_major": 2,
337
  "version_minor": 0
338
  },
339
  "text/plain": [
340
- "HBox(children=(IntProgress(value=0, description='#1', max=24, style=ProgressStyle(description_width='initial')…"
341
  ]
342
  },
343
  "metadata": {},
@@ -346,12 +507,12 @@
346
  {
347
  "data": {
348
  "application/vnd.jupyter.widget-view+json": {
349
- "model_id": "2aa538a2fdcb4d56a55cd612c879044f",
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  "version_major": 2,
351
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352
  },
353
  "text/plain": [
354
- "HBox(children=(IntProgress(value=0, description='#0', max=24, style=ProgressStyle(description_width='initial')…"
355
  ]
356
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357
  "metadata": {},
@@ -360,12 +521,12 @@
360
  {
361
  "data": {
362
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  "version_major": 2,
365
  "version_minor": 0
366
  },
367
  "text/plain": [
368
- "HBox(children=(IntProgress(value=0, description='#2', max=24, style=ProgressStyle(description_width='initial')…"
369
  ]
370
  },
371
  "metadata": {},
@@ -374,12 +535,12 @@
374
  {
375
  "data": {
376
  "application/vnd.jupyter.widget-view+json": {
377
- "model_id": "dcaa10621a674699a7bf17357cd75a4a",
378
  "version_major": 2,
379
  "version_minor": 0
380
  },
381
  "text/plain": [
382
- "HBox(children=(IntProgress(value=0, description='#4', max=24, style=ProgressStyle(description_width='initial')…"
383
  ]
384
  },
385
  "metadata": {},
@@ -388,12 +549,12 @@
388
  {
389
  "data": {
390
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391
- "model_id": "9ee2184681db4e16802387bbc1acfef3",
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  "version_major": 2,
393
  "version_minor": 0
394
  },
395
  "text/plain": [
396
- "HBox(children=(IntProgress(value=0, description='#3', max=24, style=ProgressStyle(description_width='initial')…"
397
  ]
398
  },
399
  "metadata": {},
@@ -402,12 +563,12 @@
402
  {
403
  "data": {
404
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405
- "model_id": "36c3bcde96114167a1dc6942d9d551f1",
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407
  "version_minor": 0
408
  },
409
  "text/plain": [
410
- "HBox(children=(IntProgress(value=0, description='#6', max=24, style=ProgressStyle(description_width='initial')…"
411
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412
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413
  "metadata": {},
@@ -416,12 +577,12 @@
416
  {
417
  "data": {
418
  "application/vnd.jupyter.widget-view+json": {
419
- "model_id": "b0ad190f479d40a599e74cfa9deddec8",
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421
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422
  },
423
  "text/plain": [
424
- "HBox(children=(IntProgress(value=0, description='#5', max=24, style=ProgressStyle(description_width='initial')…"
425
  ]
426
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427
  "metadata": {},
@@ -430,7 +591,7 @@
430
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431
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432
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433
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434
  "version_major": 2,
435
  "version_minor": 0
436
  },
@@ -462,11 +623,11 @@
462
  },
463
  {
464
  "cell_type": "code",
465
- "execution_count": 10,
466
  "metadata": {
467
  "ExecuteTime": {
468
- "end_time": "2021-03-14T19:33:14.391497Z",
469
- "start_time": "2021-03-14T19:33:11.216118Z"
470
  }
471
  },
472
  "outputs": [
@@ -474,8 +635,120 @@
474
  "name": "stderr",
475
  "output_type": "stream",
476
  "text": [
477
- "Using custom data configuration el-ac779bf2c9f7c09b\n",
478
- "Reusing dataset common_voice (/home/earendil/.cache/huggingface/datasets/common_voice/el-ac779bf2c9f7c09b/6.1.0/32954a9015faa0d840f6c6894938545c5d12bc5d8936a80079af74bf50d71564)\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
479
  ]
480
  }
481
  ],
@@ -536,6 +809,96 @@
536
  "# πού θέλεις να πάμε; ρώτησε φοβισμένα ο βασιλιάς."
537
  ]
538
  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
539
  {
540
  "cell_type": "code",
541
  "execution_count": null,
 
5
  "execution_count": 1,
6
  "metadata": {
7
  "ExecuteTime": {
8
+ "end_time": "2021-03-17T11:10:25.794375Z",
9
+ "start_time": "2021-03-17T11:10:24.301013Z"
10
  }
11
  },
12
  "outputs": [
 
36
  "execution_count": 2,
37
  "metadata": {
38
  "ExecuteTime": {
39
+ "end_time": "2021-03-17T11:10:29.608803Z",
40
+ "start_time": "2021-03-17T11:10:29.599700Z"
41
  }
42
  },
43
  "outputs": [],
 
75
  },
76
  {
77
  "cell_type": "code",
78
+ "execution_count": 4,
79
  "metadata": {
80
  "ExecuteTime": {
81
+ "end_time": "2021-03-17T11:11:02.120225Z",
82
+ "start_time": "2021-03-17T11:10:56.182488Z"
83
  }
84
  },
85
  "outputs": [
 
98
  },
99
  {
100
  "cell_type": "code",
101
+ "execution_count": 6,
102
  "metadata": {
103
  "ExecuteTime": {
104
+ "end_time": "2021-03-17T11:12:18.847005Z",
105
+ "start_time": "2021-03-17T11:12:14.919077Z"
106
  }
107
  },
108
  "outputs": [
 
110
  "name": "stderr",
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+ },
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+ {
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+ "name": "stdout",
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752
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753
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754
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809
  "# πού θέλεις να πάμε; ρώτησε φοβισμένα ο βασιλιάς."
810
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811
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812
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+ "text/plain": [
830
+ "HBox(children=(IntProgress(value=0, max=1522), HTML(value='')))"
831
+ ]
832
+ },
833
+ "metadata": {},
834
+ "output_type": "display_data"
835
+ },
836
+ {
837
+ "name": "stdout",
838
+ "output_type": "stream",
839
+ "text": [
840
+ "\n"
841
+ ]
842
+ }
843
+ ],
844
+ "source": [
845
+ "def map_to_result(batch):\n",
846
+ " model.to(\"cuda\")\n",
847
+ " input_values = processor(\n",
848
+ " batch[\"input_values\"], \n",
849
+ " sampling_rate=16_000, \n",
850
+ " return_tensors=\"pt\"\n",
851
+ " ).input_values.to(\"cuda\")\n",
852
+ "\n",
853
+ " with torch.no_grad():\n",
854
+ " logits = model(input_values).logits\n",
855
+ "\n",
856
+ " pred_ids = torch.argmax(logits, dim=-1)\n",
857
+ " batch[\"pred_str\"] = processor.batch_decode(pred_ids)[0]\n",
858
+ "\n",
859
+ " return batch\n",
860
+ "\n",
861
+ "results = common_voice_test.map(map_to_result)\n"
862
+ ]
863
+ },
864
+ {
865
+ "cell_type": "code",
866
+ "execution_count": 16,
867
+ "metadata": {
868
+ "ExecuteTime": {
869
+ "end_time": "2021-03-17T11:17:11.951524Z",
870
+ "start_time": "2021-03-17T11:17:08.856552Z"
871
+ }
872
+ },
873
+ "outputs": [
874
+ {
875
+ "name": "stdout",
876
+ "output_type": "stream",
877
+ "text": [
878
+ "Test WER: 0.396\n"
879
+ ]
880
+ }
881
+ ],
882
+ "source": [
883
+ "def compute_metrics(pred):\n",
884
+ " pred_logits = pred.predictions\n",
885
+ " pred_ids = np.argmax(pred_logits, axis=-1)\n",
886
+ "\n",
887
+ " pred.label_ids[pred.label_ids == -100] = processor.tokenizer.pad_token_id\n",
888
+ "\n",
889
+ " pred_str = processor.batch_decode(pred_ids)\n",
890
+ " # we do not want to group tokens when computing the metrics\n",
891
+ " label_str = processor.batch_decode(pred.label_ids, group_tokens=False)\n",
892
+ "\n",
893
+ " wer = wer_metric.compute(predictions=pred_str, references=label_str)\n",
894
+ "\n",
895
+ " return {\"wer\": wer}\n",
896
+ "\n",
897
+ "wer_metric = load_metric(\"wer\")\n",
898
+ "\n",
899
+ "print(\"Test WER: {:.3f}\".format(wer_metric.compute(predictions=results[\"pred_str\"], references= [item.lower() for item in common_voice_test_transcription['sentence']])))"
900
+ ]
901
+ },
902
  {
903
  "cell_type": "code",
904
  "execution_count": null,
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
21
  metrics:
22
  - name: Test WER
23
  type: wer
24
- value: 31.05
25
  ---
26
 
27
  # Greek (el) version of the XLSR-Wav2Vec2 automatic speech recognition (ASR) model
@@ -29,12 +29,14 @@ model-index:
29
 
30
  * language: el
31
  * licence: apache-2.0
32
- * dataset: CommonVoice (EL), 364MB: https://commonvoice.mozilla.org/el/datasets
33
- * model: XLSR-Wav2Vec2, trained for 60 epochs
34
  * metrics: Word Error Rate (WER)
35
 
36
  ## Model description
37
 
 
 
38
  Wav2Vec2 is a pretrained model for Automatic Speech Recognition (ASR) and was released in September 2020 by Alexei Baevski, Michael Auli, and Alex Conneau. Soon after the superior performance of Wav2Vec2 was demonstrated on the English ASR dataset LibriSpeech, Facebook AI presented XLSR-Wav2Vec2. XLSR stands for cross-lingual speech representations and refers to XLSR-Wav2Vec2`s ability to learn speech representations that are useful across multiple languages.
39
 
40
  Similar to Wav2Vec2, XLSR-Wav2Vec2 learns powerful speech representations from hundreds of thousands of hours of speech in more than 50 languages of unlabeled speech. Similar, to BERT's masked language modeling, the model learns contextualized speech representations by randomly masking feature vectors before passing them to a transformer network.
@@ -189,7 +191,7 @@ result = test_dataset.map(evaluate, batched=True, batch_size=8)
189
  print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
190
  ```
191
 
192
- **Test Result**: 31.05 %
193
 
194
  ### How to use for training:
195
 
@@ -200,9 +202,9 @@ Instructions and code to replicate the process are provided in the Fine_Tune_XLS
200
 
201
  | Metric | Value |
202
  | ----------- | ----------- |
203
- | Training Loss | 0.0287 |
204
  | Validation Loss | 0.6062 |
205
- | WER on CommonVoice Test *| 0.3105 |
206
  * Reference transcripts were lower-cased and striped of punctuation and special characters.
207
 
208
  Full metrics log here:
 
21
  metrics:
22
  - name: Test WER
23
  type: wer
24
+ value: 10.497628
25
  ---
26
 
27
  # Greek (el) version of the XLSR-Wav2Vec2 automatic speech recognition (ASR) model
 
29
 
30
  * language: el
31
  * licence: apache-2.0
32
+ * dataset: CommonVoice (EL), 364MB: https://commonvoice.mozilla.org/el/datasets + CSS10 (EL), 1.22GB: https://github.com/Kyubyong/css10
33
+ * model: XLSR-Wav2Vec2, trained for 50 epochs
34
  * metrics: Word Error Rate (WER)
35
 
36
  ## Model description
37
 
38
+ UPDATE: We repeated the fine-tuning process using an additional 1.22GB dataset from CSS10.
39
+
40
  Wav2Vec2 is a pretrained model for Automatic Speech Recognition (ASR) and was released in September 2020 by Alexei Baevski, Michael Auli, and Alex Conneau. Soon after the superior performance of Wav2Vec2 was demonstrated on the English ASR dataset LibriSpeech, Facebook AI presented XLSR-Wav2Vec2. XLSR stands for cross-lingual speech representations and refers to XLSR-Wav2Vec2`s ability to learn speech representations that are useful across multiple languages.
41
 
42
  Similar to Wav2Vec2, XLSR-Wav2Vec2 learns powerful speech representations from hundreds of thousands of hours of speech in more than 50 languages of unlabeled speech. Similar, to BERT's masked language modeling, the model learns contextualized speech representations by randomly masking feature vectors before passing them to a transformer network.
 
191
  print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
192
  ```
193
 
194
+ **Test Result**: 10.497628 %
195
 
196
  ### How to use for training:
197
 
 
202
 
203
  | Metric | Value |
204
  | ----------- | ----------- |
205
+ | Training Loss | 0.0545 |
206
  | Validation Loss | 0.6062 |
207
+ | WER on CommonVoice Test (%) *| 10.497628 |
208
  * Reference transcripts were lower-cased and striped of punctuation and special characters.
209
 
210
  Full metrics log here:
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