Runtime Error
Labels: triaged, bug

### 🐛 Describe the bug
Hi!, While using the simpletransformers library, I've had the following bug:

``` Bash
/opt/conda/lib/python3.7/site-packages/simpletransformers/t5/t5_model.py in train(self, train_dataset, output_dir, show_running_loss, eval_data, verbose, **kwargs)
    603                     verbose=verbose and args.evaluate_during_training_verbose,
    604                     silent=args.evaluate_during_training_silent,
--> 605                     **kwargs,
    606                 )
    607 

/opt/conda/lib/python3.7/site-packages/simpletransformers/t5/t5_model.py in eval_model(self, eval_data, output_dir, verbose, silent, **kwargs)
    700         self._move_model_to_device()
    701 
--> 702         eval_dataset = self.load_and_cache_examples(eval_data, evaluate=True, verbose=verbose, silent=silent)
...
          0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
          0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
          0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
          0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,
          0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0]))]'. Reason: 'RuntimeError('falseINTERNAL ASSERT FAILED at "/opt/conda/conda-bld/pytorch_1634272178570/work/aten/src/ATen/MapAllocator.cpp":300, please report a bug to PyTorch. unable to write to file </torch_4843_2733>')'
```

### Versions

Collecting environment information...
PyTorch version: 1.10.0
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17

Python version: 3.7.11 (default, Jul 27 2021, 14:32:16)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.19.0-38-generic-x86_64-with-debian-buster-sid
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: 
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090
Nvidia driver version: 525.105.17
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:        x86_64
CPU op-mode(s):      32-bit, 64-bit
Byte Order:          Little Endian
CPU(s):              16
On-line CPU(s) list: 0-15
Thread(s) per core:  2
Core(s) per socket:  8
Socket(s):           1
NUMA node(s):        1
Vendor ID:           GenuineIntel
CPU family:          6
Model:               158
Model name:          Intel(R) Core(TM) i9-9900K CPU @ 3.60GHz
Stepping:            12
CPU MHz:             4794.428
CPU max MHz:         5000.0000
CPU min MHz:         800.0000
BogoMIPS:            7200.00
Virtualization:      VT-x
L1d cache:           32K
L1i cache:           32K
L2 cache:            256K
L3 cache:            16384K
NUMA node0 CPU(s):   0-15
Flags:               fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] numpy==1.20.2
[pip3] torch==1.10.0
[pip3] torchelastic==0.2.0
[pip3] torchtext==0.11.0
[pip3] torchvision==0.11.1
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               11.1.74              h6bb024c_0    nvidia
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640  
[conda] mkl-service               2.4.0            py37h7f8727e_0  
[conda] mkl_fft                   1.3.1            py37hd3c417c_0  
[conda] mkl_random                1.2.2            py37h51133e4_0  
[conda] numpy                     1.20.2                   pypi_0    pypi
[conda] pytorch                   1.10.0          py3.7_cuda11.1_cudnn8.0.5_0    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torchelastic              0.2.0                    pypi_0    pypi
[conda] torchtext                 0.11.0                     py37    pytorch
[conda] torchvision               0.11.1               py37_cu111    pytorch