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ravirajoshi
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wav2vec2-large-xls-r-300m-marathi

Automatic Speech Recognition
Transformers
PyTorch
Marathi
wav2vec2
Generated from Trainer
hf-asr-leaderboard
robust-speech-event
Inference Endpoints
Model card Files Community
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@@ -2,6 +2,7 @@
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
 
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  model-index:
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  - name: wav2vec2-large-xls-r-300m-marathi
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  results: []
@@ -15,294 +16,4 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5054
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- - Wer: 0.2115
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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- - train_batch_size: 4
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- - eval_batch_size: 8
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- - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 8
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- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 500
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- - num_epochs: 10
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- - mixed_precision_training: Native AMP
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-----:|:-----:|:---------------:|:------:|
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- | 5.7504 | 0.04 | 400 | 2.5012 | 1.0481 |
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- | 1.2669 | 0.08 | 800 | 0.7129 | 0.5178 |
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- | 0.8259 | 0.12 | 1200 | 0.6041 | 0.4784 |
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- | 0.6682 | 0.16 | 1600 | 0.4670 | 0.3708 |
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- | 0.6116 | 0.2 | 2000 | 0.4416 | 0.3566 |
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- | 0.5631 | 0.24 | 2400 | 0.3988 | 0.3241 |
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- | 0.509 | 0.28 | 2800 | 0.3597 | 0.3061 |
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- | 0.4889 | 0.32 | 3200 | 0.3639 | 0.3094 |
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- | 0.4637 | 0.36 | 3600 | 0.3724 | 0.3105 |
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- | 0.4447 | 0.4 | 4000 | 0.3508 | 0.2845 |
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- | 0.4258 | 0.44 | 4400 | 0.3143 | 0.2665 |
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- | 0.4094 | 0.48 | 4800 | 0.3533 | 0.2774 |
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- | 0.3924 | 0.52 | 5200 | 0.3435 | 0.2735 |
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- | 0.3682 | 0.56 | 5600 | 0.3208 | 0.2592 |
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- | 0.383 | 0.6 | 6000 | 0.3226 | 0.2640 |
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- | 0.3707 | 0.64 | 6400 | 0.3128 | 0.2477 |
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- | 0.3459 | 0.68 | 6800 | 0.3261 | 0.2512 |
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- | 0.3373 | 0.73 | 7200 | 0.3390 | 0.2681 |
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- | 0.3311 | 0.77 | 7600 | 0.3037 | 0.2474 |
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- | 0.3273 | 0.81 | 8000 | 0.3042 | 0.2518 |
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- | 0.3131 | 0.85 | 8400 | 0.2971 | 0.2434 |
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- | 0.2997 | 0.89 | 8800 | 0.3161 | 0.2382 |
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- | 0.2955 | 0.93 | 9200 | 0.3142 | 0.2409 |
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- | 0.2962 | 0.97 | 9600 | 0.3063 | 0.2446 |
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- | 0.2747 | 1.01 | 10000 | 0.3432 | 0.2447 |
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- | 0.2468 | 1.05 | 10400 | 0.3165 | 0.2385 |
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- | 0.2455 | 1.09 | 10800 | 0.3021 | 0.2394 |
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- | 0.2421 | 1.13 | 11200 | 0.3205 | 0.2350 |
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- | 0.2429 | 1.17 | 11600 | 0.3104 | 0.2350 |
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- | 0.2406 | 1.21 | 12000 | 0.3060 | 0.2350 |
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- | 0.2508 | 1.25 | 12400 | 0.2988 | 0.2340 |
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- | 0.2263 | 1.29 | 12800 | 0.3221 | 0.2307 |
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- | 0.2211 | 1.33 | 13200 | 0.3098 | 0.2332 |
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- | 0.2198 | 1.37 | 13600 | 0.2946 | 0.2216 |
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- | 0.2197 | 1.41 | 14000 | 0.2966 | 0.2265 |
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- | 0.2188 | 1.45 | 14400 | 0.2932 | 0.2272 |
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- | 0.2165 | 1.49 | 14800 | 0.3272 | 0.2356 |
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- | 0.2147 | 1.53 | 15200 | 0.3107 | 0.2257 |
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- | 0.2063 | 1.57 | 15600 | 0.3122 | 0.2280 |
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- | 0.2034 | 1.61 | 16000 | 0.3374 | 0.2384 |
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- | 0.1965 | 1.65 | 16400 | 0.3152 | 0.2294 |
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- | 0.1854 | 1.69 | 16800 | 0.3117 | 0.2284 |
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- | 0.1869 | 1.73 | 17200 | 0.3207 | 0.2242 |
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- | 0.2088 | 1.77 | 17600 | 0.3166 | 0.2256 |
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- | 0.189 | 1.81 | 18000 | 0.3317 | 0.2231 |
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- | 0.1899 | 1.85 | 18400 | 0.3062 | 0.2232 |
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- | 0.1891 | 1.89 | 18800 | 0.3241 | 0.2284 |
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- | 0.1834 | 1.93 | 19200 | 0.3156 | 0.2292 |
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- | 0.1788 | 1.97 | 19600 | 0.3276 | 0.2237 |
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- | 0.1738 | 2.01 | 20000 | 0.3364 | 0.2146 |
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- | 0.1412 | 2.05 | 20400 | 0.3254 | 0.2190 |
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- | 0.1539 | 2.09 | 20800 | 0.3430 | 0.2246 |
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- | 0.1413 | 2.14 | 21200 | 0.3386 | 0.2262 |
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- | 0.1443 | 2.18 | 21600 | 0.3512 | 0.2266 |
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- | 0.142 | 2.22 | 22000 | 0.3271 | 0.2148 |
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- | 0.1546 | 2.26 | 22400 | 0.3290 | 0.2185 |
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- | 0.1357 | 2.3 | 22800 | 0.3599 | 0.2200 |
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- | 0.142 | 2.34 | 23200 | 0.3348 | 0.2182 |
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- | 0.1433 | 2.38 | 23600 | 0.3427 | 0.2196 |
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- | 0.1332 | 2.42 | 24000 | 0.3294 | 0.2193 |
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- | 0.1436 | 2.46 | 24400 | 0.3370 | 0.2228 |
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- | 0.134 | 2.5 | 24800 | 0.3480 | 0.2280 |
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- | 0.132 | 2.54 | 25200 | 0.3411 | 0.2230 |
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- | 0.145 | 2.58 | 25600 | 0.3305 | 0.2205 |
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- | 0.1411 | 2.62 | 26000 | 0.3450 | 0.2200 |
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- | 0.1269 | 2.66 | 26400 | 0.3412 | 0.2199 |
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- | 0.1349 | 2.7 | 26800 | 0.3445 | 0.2203 |
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- | 0.1313 | 2.74 | 27200 | 0.3406 | 0.2239 |
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- | 0.1311 | 2.78 | 27600 | 0.3501 | 0.2257 |
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- | 0.135 | 2.82 | 28000 | 0.3329 | 0.2189 |
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- | 0.1295 | 2.86 | 28400 | 0.3407 | 0.2183 |
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- | 0.1236 | 2.9 | 28800 | 0.3503 | 0.2166 |
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- | 0.1248 | 2.94 | 29200 | 0.3522 | 0.2237 |
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- | 0.122 | 2.98 | 29600 | 0.3336 | 0.2235 |
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- | 0.1158 | 3.02 | 30000 | 0.3429 | 0.2174 |
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- | 0.0999 | 3.06 | 30400 | 0.3650 | 0.2212 |
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- | 0.097 | 3.1 | 30800 | 0.3760 | 0.2231 |
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- | 0.0969 | 3.14 | 31200 | 0.3697 | 0.2231 |
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- | 0.0969 | 3.18 | 31600 | 0.3720 | 0.2223 |
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- | 0.0964 | 3.22 | 32000 | 0.3638 | 0.2192 |
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- | 0.0954 | 3.26 | 32400 | 0.3735 | 0.2211 |
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- | 0.0982 | 3.3 | 32800 | 0.3579 | 0.2252 |
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- | 0.1007 | 3.34 | 33200 | 0.3505 | 0.2200 |
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- | 0.0933 | 3.38 | 33600 | 0.3614 | 0.2318 |
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- | 0.0948 | 3.42 | 34000 | 0.3550 | 0.2203 |
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- | 0.0989 | 3.46 | 34400 | 0.3729 | 0.2245 |
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- | 0.1005 | 3.5 | 34800 | 0.3563 | 0.2267 |
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- | 0.0886 | 3.55 | 35200 | 0.3671 | 0.2217 |
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- | 0.0858 | 3.59 | 35600 | 0.3764 | 0.2169 |
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- | 0.0908 | 3.63 | 36000 | 0.3724 | 0.2226 |
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- | 0.0908 | 3.67 | 36400 | 0.3784 | 0.2288 |
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- | 0.0852 | 3.71 | 36800 | 0.3607 | 0.2193 |
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- | 0.0919 | 3.75 | 37200 | 0.3630 | 0.2192 |
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- | 0.0863 | 3.79 | 37600 | 0.3750 | 0.2258 |
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- | 0.0873 | 3.83 | 38000 | 0.3808 | 0.2170 |
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- | 0.0875 | 3.87 | 38400 | 0.3692 | 0.2225 |
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- | 0.0871 | 3.91 | 38800 | 0.3954 | 0.2249 |
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- | 0.0866 | 3.95 | 39200 | 0.3828 | 0.2204 |
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- | 0.0883 | 3.99 | 39600 | 0.3830 | 0.2249 |
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- | 0.0763 | 4.03 | 40000 | 0.3855 | 0.2177 |
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- | 0.0613 | 4.07 | 40400 | 0.4117 | 0.2264 |
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- | 0.0627 | 4.11 | 40800 | 0.3775 | 0.2215 |
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- | 0.0709 | 4.15 | 41200 | 0.3965 | 0.2227 |
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- | 0.0724 | 4.19 | 41600 | 0.3789 | 0.2141 |
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- | 0.0707 | 4.23 | 42000 | 0.3834 | 0.2193 |
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- | 0.0702 | 4.27 | 42400 | 0.3802 | 0.2216 |
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- | 0.0646 | 4.31 | 42800 | 0.3858 | 0.2141 |
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- | 0.0717 | 4.35 | 43200 | 0.3930 | 0.2184 |
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- | 0.0651 | 4.39 | 43600 | 0.3901 | 0.2170 |
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- | 0.0676 | 4.43 | 44000 | 0.4074 | 0.2158 |
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- | 0.0677 | 4.47 | 44400 | 0.3999 | 0.2164 |
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- | 0.0637 | 4.51 | 44800 | 0.3937 | 0.2241 |
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- | 0.0655 | 4.55 | 45200 | 0.4010 | 0.2248 |
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- | 0.0697 | 4.59 | 45600 | 0.4060 | 0.2236 |
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- | 0.0644 | 4.63 | 46000 | 0.4144 | 0.2179 |
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- | 0.0713 | 4.67 | 46400 | 0.3829 | 0.2172 |
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- | 0.066 | 4.71 | 46800 | 0.4152 | 0.2193 |
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- | 0.0667 | 4.75 | 47200 | 0.4015 | 0.2175 |
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- | 0.0621 | 4.79 | 47600 | 0.4058 | 0.2191 |
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- | 0.0664 | 4.83 | 48000 | 0.3898 | 0.2194 |
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- | 0.067 | 4.87 | 48400 | 0.3966 | 0.2180 |
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- | 0.0657 | 4.91 | 48800 | 0.4060 | 0.2156 |
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- | 0.0612 | 4.96 | 49200 | 0.3980 | 0.2218 |
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- | 0.0639 | 5.0 | 49600 | 0.3828 | 0.2189 |
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- | 0.0491 | 5.04 | 50000 | 0.3902 | 0.2128 |
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- | 0.0437 | 5.08 | 50400 | 0.3901 | 0.2159 |
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- | 0.0449 | 5.12 | 50800 | 0.3821 | 0.2176 |
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- | 0.0491 | 5.16 | 51200 | 0.3931 | 0.2194 |
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- | 0.0527 | 5.2 | 51600 | 0.4034 | 0.2186 |
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- | 0.0468 | 5.24 | 52000 | 0.4107 | 0.2153 |
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- | 0.047 | 5.28 | 52400 | 0.4234 | 0.2215 |
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- | 0.0516 | 5.32 | 52800 | 0.3908 | 0.2150 |
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- | 0.0495 | 5.36 | 53200 | 0.3987 | 0.2124 |
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- | 0.049 | 5.4 | 53600 | 0.4003 | 0.2140 |
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- | 0.0466 | 5.44 | 54000 | 0.4234 | 0.2176 |
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- | 0.0458 | 5.48 | 54400 | 0.4027 | 0.2195 |
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- | 0.0471 | 5.52 | 54800 | 0.4244 | 0.2235 |
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- | 0.0491 | 5.56 | 55200 | 0.4246 | 0.2223 |
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- | 0.0465 | 5.6 | 55600 | 0.4190 | 0.2233 |
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- | 0.0481 | 5.64 | 56000 | 0.4031 | 0.2181 |
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- | 0.0445 | 5.68 | 56400 | 0.4024 | 0.2171 |
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- | 0.0476 | 5.72 | 56800 | 0.4303 | 0.2230 |
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- | 0.0509 | 5.76 | 57200 | 0.4229 | 0.2232 |
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- | 0.0499 | 5.8 | 57600 | 0.4248 | 0.2237 |
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- | 0.0391 | 5.84 | 58000 | 0.4337 | 0.2232 |
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- | 0.043 | 5.88 | 58400 | 0.4243 | 0.2191 |
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- | 0.0421 | 5.92 | 58800 | 0.4376 | 0.2265 |
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- | 0.042 | 5.96 | 59200 | 0.4246 | 0.2234 |
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- | 0.0394 | 6.0 | 59600 | 0.4444 | 0.2205 |
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- | 0.0354 | 6.04 | 60000 | 0.4144 | 0.2134 |
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- | 0.0319 | 6.08 | 60400 | 0.4246 | 0.2150 |
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- | 0.0325 | 6.12 | 60800 | 0.4540 | 0.2240 |
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- | 0.0324 | 6.16 | 61200 | 0.4582 | 0.2201 |
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- | 0.0333 | 6.2 | 61600 | 0.4268 | 0.2199 |
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- | 0.0358 | 6.24 | 62000 | 0.4560 | 0.2158 |
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- | 0.0327 | 6.28 | 62400 | 0.4448 | 0.2175 |
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- | 0.0329 | 6.32 | 62800 | 0.4369 | 0.2181 |
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- | 0.0304 | 6.37 | 63200 | 0.4362 | 0.2194 |
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- | 0.0366 | 6.41 | 63600 | 0.4401 | 0.2174 |
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- | 0.0357 | 6.45 | 64000 | 0.4440 | 0.2189 |
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- | 0.0313 | 6.49 | 64400 | 0.4424 | 0.2128 |
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- | 0.0354 | 6.53 | 64800 | 0.4318 | 0.2182 |
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- | 0.0295 | 6.57 | 65200 | 0.4497 | 0.2255 |
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- | 0.0303 | 6.61 | 65600 | 0.4448 | 0.2117 |
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- | 0.03 | 6.65 | 66000 | 0.4285 | 0.2104 |
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- | 0.0325 | 6.69 | 66400 | 0.4422 | 0.2187 |
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- | 0.0302 | 6.73 | 66800 | 0.4419 | 0.2150 |
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- | 0.0335 | 6.77 | 67200 | 0.4264 | 0.2201 |
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- | 0.0306 | 6.81 | 67600 | 0.4614 | 0.2215 |
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- | 0.0321 | 6.85 | 68000 | 0.4526 | 0.2195 |
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- | 0.0349 | 6.89 | 68400 | 0.4607 | 0.2202 |
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- | 0.0277 | 6.93 | 68800 | 0.4634 | 0.2175 |
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- | 0.0346 | 6.97 | 69200 | 0.4348 | 0.2188 |
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- | 0.0332 | 7.01 | 69600 | 0.4605 | 0.2177 |
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- | 0.0271 | 7.05 | 70000 | 0.4501 | 0.2177 |
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- | 0.0244 | 7.09 | 70400 | 0.4722 | 0.2169 |
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- | 0.0258 | 7.13 | 70800 | 0.4501 | 0.2193 |
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- | 0.0224 | 7.17 | 71200 | 0.4730 | 0.2175 |
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- | 0.0254 | 7.21 | 71600 | 0.4693 | 0.2223 |
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- | 0.0257 | 7.25 | 72000 | 0.4684 | 0.2231 |
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- | 0.0206 | 7.29 | 72400 | 0.4526 | 0.2197 |
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- | 0.0276 | 7.33 | 72800 | 0.4569 | 0.2158 |
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- | 0.0212 | 7.37 | 73200 | 0.4873 | 0.2201 |
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- | 0.0233 | 7.41 | 73600 | 0.4592 | 0.2190 |
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- | 0.0231 | 7.45 | 74000 | 0.4647 | 0.2209 |
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- | 0.0202 | 7.49 | 74400 | 0.4766 | 0.2165 |
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- | 0.0218 | 7.53 | 74800 | 0.4735 | 0.2155 |
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- | 0.0198 | 7.57 | 75200 | 0.4477 | 0.2153 |
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- | 0.0222 | 7.61 | 75600 | 0.4498 | 0.2091 |
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- | 0.0228 | 7.65 | 76000 | 0.4563 | 0.2151 |
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- | 0.0214 | 7.69 | 76400 | 0.4636 | 0.2162 |
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- | 0.021 | 7.73 | 76800 | 0.4467 | 0.2146 |
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- | 0.0224 | 7.78 | 77200 | 0.4580 | 0.2171 |
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- | 0.0172 | 7.82 | 77600 | 0.4678 | 0.2141 |
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- | 0.0226 | 7.86 | 78000 | 0.4567 | 0.2133 |
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- | 0.0197 | 7.9 | 78400 | 0.4792 | 0.2162 |
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- | 0.0186 | 7.94 | 78800 | 0.4555 | 0.2174 |
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- | 0.0191 | 7.98 | 79200 | 0.4593 | 0.2164 |
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- | 0.0175 | 8.02 | 79600 | 0.4725 | 0.2181 |
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- | 0.0136 | 8.06 | 80000 | 0.4716 | 0.2148 |
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- | 0.0155 | 8.1 | 80400 | 0.4723 | 0.2143 |
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- | 0.016 | 8.14 | 80800 | 0.4632 | 0.2091 |
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- | 0.016 | 8.18 | 81200 | 0.4853 | 0.2153 |
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- | 0.0162 | 8.22 | 81600 | 0.4717 | 0.2176 |
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- | 0.0162 | 8.26 | 82000 | 0.4638 | 0.2179 |
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- | 0.013 | 8.3 | 82400 | 0.4661 | 0.2153 |
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- | 0.0151 | 8.34 | 82800 | 0.4745 | 0.2144 |
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- | 0.0147 | 8.38 | 83200 | 0.4694 | 0.2143 |
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- | 0.0124 | 8.42 | 83600 | 0.4776 | 0.2156 |
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- | 0.0129 | 8.46 | 84000 | 0.4754 | 0.2156 |
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- | 0.0147 | 8.5 | 84400 | 0.4770 | 0.2193 |
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- | 0.0143 | 8.54 | 84800 | 0.4585 | 0.2167 |
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- | 0.0135 | 8.58 | 85200 | 0.4832 | 0.2215 |
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- | 0.013 | 8.62 | 85600 | 0.4736 | 0.2202 |
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- | 0.0124 | 8.66 | 86000 | 0.4861 | 0.2203 |
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- | 0.0123 | 8.7 | 86400 | 0.4794 | 0.2189 |
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- | 0.0162 | 8.74 | 86800 | 0.4827 | 0.2186 |
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- | 0.0132 | 8.78 | 87200 | 0.4688 | 0.2163 |
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- | 0.0119 | 8.82 | 87600 | 0.4682 | 0.2157 |
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- | 0.012 | 8.86 | 88000 | 0.4611 | 0.2147 |
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- | 0.0113 | 8.9 | 88400 | 0.4841 | 0.2152 |
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- | 0.0138 | 8.94 | 88800 | 0.4841 | 0.2160 |
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- | 0.0128 | 8.98 | 89200 | 0.4901 | 0.2170 |
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- | 0.0099 | 9.02 | 89600 | 0.4744 | 0.2141 |
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- | 0.0087 | 9.06 | 90000 | 0.4894 | 0.2149 |
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- | 0.0083 | 9.1 | 90400 | 0.4797 | 0.2131 |
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- | 0.0085 | 9.14 | 90800 | 0.4842 | 0.2138 |
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- | 0.0104 | 9.19 | 91200 | 0.4754 | 0.2135 |
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- | 0.0091 | 9.23 | 91600 | 0.4813 | 0.2140 |
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- | 0.0108 | 9.27 | 92000 | 0.4829 | 0.2139 |
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- | 0.0121 | 9.31 | 92400 | 0.4905 | 0.2139 |
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- | 0.008 | 9.35 | 92800 | 0.4940 | 0.2147 |
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- | 0.0114 | 9.39 | 93200 | 0.4925 | 0.2148 |
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- | 0.008 | 9.43 | 93600 | 0.5015 | 0.2149 |
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- | 0.0089 | 9.47 | 94000 | 0.5049 | 0.2145 |
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- | 0.0088 | 9.51 | 94400 | 0.5087 | 0.2156 |
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- | 0.0076 | 9.55 | 94800 | 0.5092 | 0.2165 |
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- | 0.0092 | 9.59 | 95200 | 0.5097 | 0.2151 |
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- | 0.0076 | 9.63 | 95600 | 0.5042 | 0.2141 |
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- | 0.0084 | 9.67 | 96000 | 0.5060 | 0.2142 |
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- | 0.0099 | 9.71 | 96400 | 0.5066 | 0.2127 |
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- | 0.0086 | 9.75 | 96800 | 0.5057 | 0.2123 |
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- | 0.0069 | 9.79 | 97200 | 0.5075 | 0.2128 |
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- | 0.0071 | 9.83 | 97600 | 0.5045 | 0.2122 |
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- | 0.0073 | 9.87 | 98000 | 0.5064 | 0.2119 |
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- | 0.0073 | 9.91 | 98400 | 0.5057 | 0.2120 |
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- | 0.0091 | 9.95 | 98800 | 0.5063 | 0.2116 |
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- | 0.0077 | 9.99 | 99200 | 0.5054 | 0.2115 |
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- ### Framework versions
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-
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- - Transformers 4.16.0.dev0
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- - Pytorch 1.10.1+cu102
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- - Datasets 1.17.1.dev0
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- - Tokenizers 0.11.0
 
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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+ - robust-speech-event
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  model-index:
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  - name: wav2vec2-large-xls-r-300m-marathi
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  results: []
 
16
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
  - Loss: 0.5054
19
+ - Wer: 0.2115